UNSW Science Vacation Research Scholarship UGVC1056
2019/2020 Research Projects

The UNSW Science Summer Vacation Research Scholarship UGVC1056 exposes highly talented undergraduate students, enrolled in Science or a related discipline, to scientific research and other science-based experience, and to further their education and inspire them to consider research or related activities. The scholarship program will run for a six week period over the Summer Semester (November to February).

 

How to apply

To apply you will need to submit the following:

Supporting Documentation

Please submit the following with your Scholarship application:

  • An electronic copy of your CV
  • An electronic copy of your academic transcript

Applications are now open and will close Friday 20 September 2019.

Research Projects

Click on the School to view possible research projects:

Aviation

Project Title: Remotely Piloted Aircraft ("Drones") for Sustainable Destination Management

Supervisor(s): Tay Koo, Senior Lecturer, School of Aviation

Description: The student will be involved in developing a framework for the usage of drones for sustainable destination management in the context of an environmentally protected area.

Student will receive necessary training and induction on school equipment, and will undertake both field and desk-based research.

The former will involve data collection using drone equipment whereas the latter will involve finding and reviewing relevant research literature.

By the end of the summer vacation research program, the student will be expected to have produced a written report that can be used by an industry partner organisation involved in protected area management in Australia.


 

 

Biotechnology and Biomolecular Sciences

Project Title: Engineering novel protein-based biosensors

Supervisor(s): Dr Dominic Glover

Description: Living cells are filled with proteins and other molecules that can serve as “building blocks” for scientists to assemble functional devices, such as biosensors for the detection of toxic pollutants. Typical biosensors make use of complicated genetic circuits that allow cells to probe their environment for specific molecules and then compute the results. However, such circuits involve several rounds of transcription, translation and regulatory events that slow down the response time. In this project, students will produce and characterise protein components that will be used to replace synthetic gene circuits with synthetic protein circuits. Ultimately, protein circuits are expected to improve the sensitivity and response time of biosensors, as well as reducing the number of “parts” required to build a biodevice.

Note: Students majoring in molecular biology or a related field, and an interest in synthetic biology or bioengineering. 


 

Project Title: Nutigenomics and selection

Supervisor(s): Prof Bill Ballard and Samuel Towarnicki

Description: Nutrigenomics is the study of the interactions of diet and the genome. In this project we ask if differential fitness may be explained through diet by genome interactions, and may influnce the frequency of Drosophila melanogaster flies in nature. This project has implications for our understanding of human dieseases that involve interactions of diet and genome, such as diabetes and obestiy.

Note: For students finishing second year and has an interest in genetics.


 

Project Title: GGT purification and immobilisation

Supervisor(s): Dr Christopher Marquis and Dr Wallace Bridge

Description: In this project we aim to further develop an immobilised gamma glutamyltransferase (GGT) for application in peptide synthesis. This project will utilise various protein production and purification techniques in the UNSW Recombinant Products Facility. Different immobilisation methods will be trialled and various reactor configurations for immobilised enzyme bioconversion will be evaluated.

Note: For Students who have some background in chemistry, biochemistry or biotechnology.


 

Project Title: Deep omics!

Supervisor(s): Dr Fatemeh Vafaee

Description: Deep learning has revolutionized research in image processing and speech recognition and will soon transform research in molecular biomedicine. Deep learning models can capture multiple levels of representation directly from raw data without the need to carefully engineer features based on fine-tuned algorithmic approaches or domain expertise. Omics data is one of the most prominent examples of feature‐rich and high‐dimensional heterogeneous data and thus multi-omics data analysis and integration have increasingly become a deep learning harvesting field in computational biology. We are developing deep learning models to leverage large omics data for finding hidden structures within them, for integrating heterogeneous data and for making accurate predictions in different biomedical applications ranging from single-cell omics analysis and multi-omics biomarker discovery to human functional genomics and drug discovery.

For more information, visit: http://vafaeelab.com/index.html

Note: Students with computational background having interest/experience in biomedical applications. Students with experience in machine learning and/or bioinformatics


 

Project Title: Diploid yeast genome assembly

Supervisor(s): Dr Richard Edwards

Description: Long read sequencing offers the prospect of fully resolving both copies of diploid genomes during whole genome assembly. This project will assist in the assembly and haplotype phasing of diploid yeast genomes that were sequenced as part of an industrial collaboration to identify the genetic basis of experimentally evolved novel metabolism.

Note: Students should have an interest in genomics/genetics and bioinformatics. Some prior experience of commandline tools would be very beneficial.

This project is 100% computational.


 

Project Title: Protein-protein interaction motif prediction from cross-link mass spectrometry

Supervisor(s): Dr Richard Edwards

Description: Many protein-protein interactions are mediated by short linear motifs (SLiMs). This project will integrate SLiM prediction tools with sites of interaction that have experimentally identified through cross-linking mass spectrometry (XL-MS), in collaboration with Prof Marc Wilkins. The goal is to investigate how useful XL-MS data is for SLiM discovery.

Note: Students majoring in Biochemistry, Molecular Biology or Bioinformatics. Prior experience or an interest in programming and/or RStudio would be beneficial.

This project is 100% computational.


 

Project Title: Rare disease gene discovery

Supervisor(s): Dr Emily Oates

Description: Our research is focused on the discovery of new human disease genes, establishing the biological pathways that are impacted by mutations in these genes, and using this information to identify targets for future therapies. In this summer project students will have the opportunity of analysing massively parallel genetic sequencing data from patients with rare genetic disorders who do not currently have a genetic diagnosis. In most cases patient data will be analysed in parallel with data from both unaffected parents to increase the chance of identifying the causative mutation(s) (“trio” analysis). If potentially pathogenic variants in possible new disease genes are identified, students will draw on existing literature and database-accessible information to determine the biological plausibility of the gene as a disease gene (e.g. Is the gene expressed in the clinically affected tissues?, Does the gene encode a protein involved in a pathway altered in other similar diseases?). The student will also determine the likely pathogenicity of their variants of interest using in silico-based analytical techniques, and by finding additional patients with mutations within the same gene via our well-established collaborator network and clinical ‘matchmaking’ programs.

Note: Third year students with a background in genetics and an interest in human genetics. Bioinformatics/programming skills useful but not essential.


Project Title: Investigating the biological relevance of i-Motif RNA

Supervisor(s): Prof. Marcel Dinger and Dr. Mahdi Zeraati

Description: Cytosine-rich sequences can form i-Motif structure. We have recently demonstrated that i-Motif DNA structures are formed in the nuclei of human cells and may have regulatory functions. In general, i-Motif RNA structures are less stable than their DNA counterparts and no regulatory function has been assigned to them. In this project, we will investigate sequences in the human transcriptome that can form i-Motif RNA with the ultimate goal of understanding their regulatory roles.

Note: For Students with an interest/background in molecular genetics and biotechnology.

Biological, Earth and Environmental Sciences

School of Biological, Earth and Environmental Sciences

 

Project Title: Where does the Letter winged kite find refuge during drought?

Supervisor(s): Professor Mike Letnic, Associate Professor Shawn Laffan, Charlotte Mills

Description: The Letter-winged kite is a nomadic nocturnal bird of prey. Previous studies of letter-winged kites have shown that populations of these predators typically track rainfall driven irruptions of rodents which are an important prey item for kites. However, nearly all information available on the ecology of letter-winged kites comes from the “good-times” after high rainfall events when small mammal prey are abundant across much of the continent. In contrast, we have a poor understanding of where and how letter-winged kites survive during droughts. This student vacation project will investigate where and how letter-winged kites survive drought periods using a combination of laboratory analyses of kite diets and interrogation of citizen science databases.  We are seeking an enthusiastic student with a background in ecology or geography. The successful candidate will obtain skills in microscopy, identification of vertebrates and invertebrates, ArcGIS and R.


 

Project Title: Using tree rings to look into the desert’s past

Supervisor(s): Daniel Falster, Mike Letnic

Description: Due to poor preservation there are very few records available to look into the palaeoecology of the Australian arid zone. The record provided by growth rings of long-lived trees provides a potential way to investigate past rainfall and environmental events in arid Australia. However, few studies have used tree rings to examine environmental history in arid Australia. This student vacation project will investigate the environmental history of arid Australia by examining the structure of wood in cross-sections of mulga trees (Acacia aneura). We are seeking an enthusiastic student with a background in ecology or geography. The successful candidate will obtain skills in digital image analysis, microscopy and R.


 

Project Title: Conservation and restoration of threatened plants using indigenous soil microbes

Supervisor(s): Dr Miriam Munoz-Rojas, Dr Mark Ooi 

 

Description: The depletion and degradation of native plant communities is a major threat to long-term health and functionality of Australian ecosystems. Current challenges in conservation and restoration programs are poor recruitment and establishment of threatened plants. Over 1,100 Australian plant species are threatened, and more than 60 are thought to be extinct. Thus, finding solutions for increasing the capacity of native plants to survive and grow is key to improving the success of conservation and restoration programs. This project will investigate the capacity of Australian indigenous soil microbes, including cyanobacteria from soil biocrusts, to promote germination and growth of native threatened plants and improve bacteria inoculants for application in large-scale conservation and restoration programs. Students in this project will assist in developing novel eco-engineering, seed enhancement and bio-priming technologies for application in conservation and restoration programs.


 

Project Title: In the spotlight: impacts of artificial light at night on the marine environment

Supervisor(s): Dr Mariana Mayer-Pinto, Dr Katherine Dafforn, Prof Alistair Poore

Description: More than 20% of the world’s coastlines are estimated to be exposed to artificial night-time lighting (ALAN). Despite increasing evidence of the immediacy, severity and the phylogenetic breadth of night-time lighting impacts, ALAN is expected to increase globally in both intensity and spatial extent in the coming decades. However, the potential impacts of this emerging threat on the overall ecology of coastal communities is still largely unknown. This project aims to address these knowledge gaps by assessing how ALAN affects the overall diversity and functioning of coastal urbanised systems.


  

Project Title: Foreshore stabilisation and potential ecological consequences of different types of interventions

Supervisor(s): Dr Mariana Mayer-Pinto, Dr Katherine Dafforn

Description: Rocky intertidal cobble and boulder foreshores provide an important diversity of microhabitats for animals living along the shoreline and have the potential to reduce wave energy, enable the transport of wrack deposits offshore, and overall enhance sediment stabilisation for improvements in water quality. However, in urban estuaries and ICOLLs much of this habitat has been lost through channel and escarpment modifications or modified by seawall construction. This is apparent in Lake Macquarie where past developments along the foreshore have created water quality problems from eroding sediments as well as trapped and decaying wrack along the strandline. Since 1999, the Lake Macquarie Estuary Management Plan has adopted a “soft engineering” approach and has added boulders and cobbles to multiple sites around the foreshore for sediment stabilisation and to match the naturally present cobble beaches that historically provided the dominant habitat. However, the effectiveness of these interventions regarding shoreline stabilisation and potential impacts on the local diversity and functioning are yet to be assessed using robust methodology. This project will assess the ecological benefits of the Foreshore Stabilisation Program. This project will be in collaboration with and supported by the NSW Office of Environmental and Heritage and the Lake Macquarie Council, therefore the student will be able to gain experience that is relevant to careers within and outside academia.


 

Project Title: Crowdsourcing air temperature variability in the Sydney area using citizen weather stations

Supervisor(s): Dr Negin Nazarian, Dr Melissa Hart

Description: Observational networks at high spatial resolution and over long time periods remains a challenge in urban climate research. The emergence of low-cost Internet-of-Things sensing units presents a new approach for addressing such challenges and contributes to investigating the variability in urban microclimate with less centralized efforts. This study aims to evaluate the air temperature data crowdsourced from such sensing units, Netatmo’ citizen weather stations (CWS), used at multiple locations around Sydney area and analyze its application for monitoring the urban climate in this region. Additionally, the impact of urban form and landscaping type, determined by local climate zone (LCZ) classification done at CCRC), on the microclimate of the Sydney area can also be assessed using crowdsourced data. Overall, the objective of this study is to evaluate a) the quality CWS data compared with the SWAQ sensing units, b) assess the intra-LCZ temperature variability of air temperature to determine if significant correlations can be detected between urban characteristics and temperature.


  

Project Title: The effect of the Millennium drought on land

Supervisor(s): Dr Sanaa Hobeichi (UNSW) and Dr Gab Abramowitz (UNSW)

Description: The Millennium drought devastated much of Southern Australia during 1996-2010 and altered the water and energy cycles on the land surface. These cycles play an important role in influencing the climate and determining how the drought impacts are felt on land by humans and ecosystems (Yin et al., 2014). This project will explore changes in two key energy and water variables during the Millennium drought: latent heat flux (LH) and sensible heat flux (SH). These variables help us understand the drought impacts on the land and have been measured by flux towers in different regions over Australia, together with net radiation and ground heat flux.

In this project, you will learn more about the effects of the Millennium drought on the surface energy budget, particularly on the ratio of sensible heat flux to latent heat flux (i.e. SH/LH). You will use measurements taken during the drought period (2000 – 2010) and after the drought period, from both impacted and non-impacted sites to guide analysis and conclusions. The flux measurements will also be used to evaluate the ability of gridded estimates of sensible and latent heat fluxes (e.g. FLUXCOM; Jung et al., 2018) - which are based on satellite observations rather than direct measurements - to capture this drought event


 

Project Title: Assessing regional climate model capabilities to add value to global climate model projections of Australian heatwaves

Supervisor(s): Dr Giovanni Di Virgilio (UNSW) and Dr Annette Hirsch (UNSW)

Description: Heatwaves are periods of excessively hot weather, which when severe have caused crop failures, power outages and result in more deaths in Australia than any other natural hazard. If global temperatures continue to rise as predicted, heatwaves will become more frequent, intense and last longer. Global climate models (GCMs) produce climate projections that are used by governments and businesses to plan for a future climate conducive to more extreme heatwaves, however, the coarse spatial resolution of GCMs cannot resolve the fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when RCMs provide improved information about both historical and projected heatwaves relative to driving GCMs is lacking. This project aims to discover where and when RCMs improve (or not) on the simulation of Australian heatwaves, relative to their host GCMs. Understanding this is vital to adaptation planning for extreme weather like heatwaves. The student will work on this project with Dr Giovanni Di Virgilio (UNSW) and Dr Annette Hirsch (ANU). Experience of programming in Python or similar for data analysis is essential; familiarity with high performance computing is desirablet


  

Project Title: Changes in hydrological extremes across Australia under future climate change

Supervisor(s): Elisabeth Vogel (BOM), Louise Wilson (BOM), Anna Ukkola (ANU), Margot Bador (UNSW)

Description: Climate change affects the frequency and severity of certain hydrological extremes, such as the risk of flooding events or soil moisture drought. These changes in hydrological extremes are a concern for many sectors that are highly dependent on hydrological conditions, such as water resources management, infrastructure or agriculture. In order to prepare for these changes, it is crucial to gain a better understanding of the spatial and temporal pattern of climate change impacts on hydrological extremes.

The aim of this student project is to investigate the impacts of climate change on hydrological extremes, such as high runoff events, hydrological or agricultural drought. It uses outputs of the AWRA-L hydrological model, which underpins the BoM's Australian Landscape Water Balance website. The model simulates the land surface water balance and outputs hydrological stores and fluxes, including run-off, evapotranspiration and soil moisture in three soil layers (0m–0.1m, 0.1m–1.0m, 1.0m–6.0m). As part of the Bureau's Hydrological Projections project, AWRA-L was forced with an ensemble of climate data based on: a) two scenarios for future greenhouse gas concentrations, b) four general circulation models (GCM) that have been assessed to be skilful for the Australian domain, and c) a range of statistical and dynamical bias-correction and downscaling methods. Using the data, the student will a) investigate changes in selected hydrological extreme indicators between the past and future, and b) analyse uncertainties in the projections related to GCM selection, bias-correction and downscaling method, and emission scenarios.

The student will be based at the Bureau of Meteorology in Melbourne (other Bureau offices might be possible). The project would ideally suit a student with some experience in programming and data visualisation (e.g. using Python, R, Matlab). Experience in working with large datasets (e.g. on the NCI) would be preferable. The timing of the project can be arranged flexibly with the student


 

Project Title: The effect of bias correction and downscaling methods on hydrological projections

Supervisor(s): Justin Peter (BOM), Pandora Hope (BOM), Anna Ukkola (ANU), Lisa Alexander (UNSW)

Description: Hydrological impact studies analyse the effects of climate change on hydrological variables, such as changes in soil moisture, streamflow or hydrological extremes. Such studies are important, for example, for ensuring sustainable water resources management, agriculture or infrastructure development. Hydrological impact assessments are commonly based on hydrological models forced with corrected outputs of general circulation models (GCMs) that simulate future climate conditions, including temperature, precipitation, wind or solar radiation, under a range of possible scenarios for future greenhouse gas concentrations (e.g. CMIP outputs). Due to very high computing requirements of climate simulations, the model outputs are typically available at relatively coarse resolution – coarser than is needed to force hydrological models. In addition, small-scale processes that are below the climate model resolution are approximated using parameterisations, leading to potential biases in some variables or processes. To overcome these issues, bias-correction and downscaling methods have been developed to remove any systemic biases and to increase the resolution of the model output to match the spatial resolution required by the impact models.

The aim of this student project is to investigate the effect of such bias correction and downscaling methods on hydrological projections for Australia. The Bureau of Meteorology (BoM) is currently developing a National Hydrological Projections Service that will provide estimates of future climate change impacts on Australian water resources, based on four general circulation models (GCM) and a range of statistical and dynamical bias-correction and downscaling methods. The following statistical bias correction and downscaling methods have been applied to raw GCM outputs: 1) a trend-preserving quantile matching approach developed for the Intersectoral Impacts Model Intercomparison Project (ISIMIP) (Hempel, Frieler, Warszawski, Schewe, & Piontek, 2013), 2) a statistical downscaling method (SDM) developed at the Bureau of Meteorology (Timbal, Fernandez & Li, 2009), 3) a multi-variate bias-correction and spatial disaggregation (rBCSD) method (Mehrotra & Sharma, 2016; Nahar & Sharma, 2017), and 4) a quantile matching empirical statistical downscaling method optimised for preserving extreme events (Dowdy, 2019).

Focusing on selected hydrological indicators (e.g. the frequency and severity of heavy precipitation events, drought frequency, severity or duration) and on key catchments across Australia, the student will investigate two research questions: 1) To which degree do bias correction and downscaling methods improve the agreement of climate model data with observations in terms of the frequency and severity of hydrological extremes (spatially and temporally) in the historical period? 2) How do bias correction and downscaling methods affect the agreement between climate simulations for future climate change impacts on hydrological extreme indicators?

The student will be based at the Bureau of Meteorology in Melbourne (other Bureau offices might be possible). The project would ideally suit a student with some experience in programming and data visualisation (e.g. using Python, R, Matlab). Experience in working with large datasets (e.g. on the NCI) would be preferable. The timing of the project can be arranged flexibly with the student.


 

Project Title: The role of soil moisture drought for wheat production in Australia

Supervisor(s): Elisabeth Vogel (BOM), Lisa Alexander (UNSW)

Description: Australian wheat production is highly water-limited and wheat yields correlate strongly with precipitation amounts during the growing season. Australia is one of the top wheat producers in the world; therefore, impacts on Australian wheat production from hydrological extremes are not only felt locally, but can potentially have effects on global wheat trade.

Under certain conditions, periods of below-average rainfall may not immediately lead to negative yield impacts, as crops source water from the soil, leading to reduced or lagged impacts. Other indicators, capturing soil moisture drought, may therefore be better predictors of yield losses. One potential advantage is that, due to soil memory effects, seasonal forecasts of soil moisture can have higher skill compared to precipitation forecasts, especially during dry periods, and may therefore offer promising potential for informing seasonal forecasts of wheat yields in Australia.

The Bureau of Meteorology (BoM) is currently developing a seasonal forecasting system of hydrological variables for Australia, using the AWRA-L land surface water balance model, forced with seasonal climate forecasts of precipitation, temperature, solar radiation and wind from the ACCESS-S model. The aim of this student project is to investigate the relationships between hydrological extremes (especially soil moisture drought) and wheat production in Australia. The outcome of the project may inform the development seasonal forecasts of hydrological indicators for agricultural production in Australia.

The project is divided into two parts:

1)     The first part investigates the upper limit of predictability of wheat yields using soil moisture, precipitation, temperature and solar radiation. It aims to investigate to which degree variations in wheat yield and production in Australia are explained by variations in soil moisture, temperature and solar radiation (using historical, observed data). Does using soil moisture data improve the statistical predictions compared to using precipitation data?

2)     In the second part, the student may use retrospective seasonal forecasts (called hindcasts) of soil moisture, as well as climate variables, to assess the usefulness of hydrological forecasts for predicting yield losses in Australia at varying lead times.

The student will be based at the Bureau of Meteorology in Melbourne (other Bureau offices might be possible). The project would ideally suit a student with some experience in programming and data visualisation (e.g. using Python, R, Matlab). Experience in working with large datasets (e.g. on the NCI) would be preferable. The timing of the project can be arranged flexibly with the student.


 

Project Title: Identifying the cumulative burden of air pollution on human health in a climate changed Australia

Supervisor(s): Donna Green

Description: The cumulative burden of air pollution on human health in Australia’s cities is not known. As climate change affects air pollution, it is anticipated that the future impacts on human health will be exacerbated. This project will explore different methods of assessing cumulative exposure to air pollution in order to make suggestions as to how we might best make policy recommendations that protect the health of all Australians, including vulnerable communities


 

Project Title: Drought termination and extreme precipitation in Australia

Supervisor(s): Dr Nina Nadine Ridder (UNSW) and Dr Anna Ukkola (UNSW)

Description: Drought is one of the major natural hazards affecting Australia. Continuous drought conditions can significantly affect soil moisture and with this the ability of soil to absorb precipitation. As such, if a drought is terminated by extreme precipitation the risk of flash flooding is increased as less water is able to infiltrate into the dry soils.

This student project will determine the probability of a drought being terminated by an extreme precipitation event to assess the risk of drought-induced flooding. For this the student will assess observations, reanalysis data and results from a large climate model ensemble.

Requirements: Some prior programming experience (e.g. Python, MATLAB, R, etc.) or a willingness to learn.


 

Project Title: Spatially correlated extreme events in Australia over the past 30 to 40 years

Supervisor(s): Dr Nina Nadine Ridder and TBA

Description: Many weather and climate extremes are combinations of multiple hazards, which act together and tend to exacerbate the socio-economic impact of an event. Events that are the result of multiple hazards acting together are known as Compound Events. One type of Compound Events are spatially correlated events. These events consist of weather extremes taking place at several locations simultaneously (or in one season) and are of particular importance for first responders who need to manage their resources and the dispatchment of forces.

This student project will focus on spatially correlated events in Australia that occurred in the past 30 to 40 years. Using observations over this time period the student will

  • catalogue past compound events,
  • assess possible trends in their occurrence,
  • check for preferred spatial correlation patterns, and
  • assess if these were accurately reproduced in reanalysis products (e.g. BARRA, ERA-5 and/or ERA-Interim).

Depending on student interest possible hazards to assess are (but are not limited to) extreme precipitation, extreme temperatures/heatwaves, bushfires, wind storms, and/or droughts.

Requirements: Some prior programming experience (e.g. Python, MATLAB, etc.) or a willingness to learn


 

Project Title: How well can we reconstruct past ocean circulation?

Supervisor(s): Dr Lise Missiaen

Description: The ocean is a key component of the climate system because it can modulate the Earth's energy balance and the atmospheric CO2 content. Climate models predict a slowdown of the Atlantic ocean circulation in response to the current global warming. However the uncertainties remain substantial and the modern instrumental record too short (a few decades) to fully capture the possible ocean circulation modes.

Longer ocean circulation records can be derived from indirect evidence (e.g. elemental or isotopic analysis of the sediments) called proxies. There is compelling evidence that under different climate states (e.g. glacial-interglacial cycles), the Atlantic Ocean has experienced significant water mass reorganisations and circulation changes. This project aims at better constraining these variations, using models able to simulate proxy variations.

The project will use climate model simulations in which the circulation has been perturbed. The student will first explore and characterise the Atlantic ocean circulation and its variability and then compare to the simulated proxies.

Requirements: Some experience of/or interest in developing skills in programming and data visualisation (e.g. ferret, python) is required. Interest in/willingness to learn about paleoclimate and/or ocean circulation is a plus.


 

Project Title: Marine heatwaves

Supervisor(s): Dr Alex Sen Gupta and Dr Andrea Taschetto

Description: Marine heatwaves have received far less attention that their terrestrial counterparts. Yet they can have devastating effects on marine ecosystems. While interest in here events is growing there are still many unanswered questions. In this project we will look at one of the two following questions: (1) Do marine heatwaves occur preferentially in certain seasons, and if so why? (ii) Do marine heatwaves produce a consistent response in ocean primary production?

The successful candidate would need to have good skills in data analysis and the ability to work with either Matlab or Python (or equivalent).


Chemistry

Project Title: New basis sets for high-quality ab initio calculations of NMR spin-spin coupling constants

Supervisor(s): Dr Laura McKemmish

Description: Nuclear magnetic resonance (NMR) is a ubiquitous technique extensively utilised throughout the sciences, but most especially by the synthetic chemistry community. Standard techniques of analysing these important spectra often fail for fluoro-organic compounds due to the strong influence of the fluorine atom on nearby nuclei. Computational chemistry can be of significant assistance in enabling accurate assignment and interpretation of the NMR spectra of fluoro-organic compounds. However, existing techniques struggle to model the very important core electron region of the molecule; our new approach is a fundamental change to the existing paradigm that has the potential to revolutionise our ability to model the core electron region and thus dramatically increase the quality of ab initio predictions of NMR spin-spin coupling constants.
This project will involve computational chemistry, use of a supercomputing cluster and basic programming (such as command line and Python).


 

Project Title: The development of novel organocatalytic methods and applications in organic synthesis

Supervisor(s): Dr Vinh Nguyen

Description: Organocatalysis, chemical processes catalyzed by small non-metallic organic compounds, has recently emerged as one of the most promising fields in organic chemistry. It can be employed in diverse synthetic cascade sequences to quickly construct complex bonds, stereocenters and polycyclic frameworks. The Nguyen group has pioneered the concept of using the tropylium ion as a novel organocatalyst for several organic reactions. Tropylium ions possess an interesting combination of structural stability and chemical reactivity due to its Hückel aromaticity and its positively charged polyene nature, respectively, which make them attractive catalytic systems. We have also exploited the chemical versatility and unique structural properties of the tropylium ion to derive family of novel push–pull organic dyes with strong absorption in the visible range via simple and practical synthetic protocols. These stable organic dyes are highly stimuli‐responsive, as demonstrated by their sensitivity towards solvent, pH change, redox reaction, Lewis base and counterion, which marks them as potentially useful compounds for optoelectronic applications.

For further details on Nguyen’s group research, visit http://tvnguyengroup.wordpress.com/


 

Project Title: Construction of novel advanced functional materials from interesting organic building blocks

Supervisor(s): Dr Vinh Nguyen

Description: Organocatalysis, chemical processes catalyzed by small non-metallic organic compounds, has recently emerged as one of the most promising fields in organic chemistry. It can be employed in diverse synthetic cascade sequences to quickly construct complex bonds, stereocenters and polycyclic frameworks. The Nguyen group has pioneered the concept of using the tropylium ion as a novel organocatalyst for several organic reactions. Tropylium ions possess an interesting combination of structural stability and chemical reactivity due to its Hückel aromaticity and its positively charged polyene nature, respectively, which make them attractive catalytic systems. We have also exploited the chemical versatility and unique structural properties of the tropylium ion to derive family of novel push–pull organic dyes with strong absorption in the visible range via simple and practical synthetic protocols. These stable organic dyes are highly stimuli‐responsive, as demonstrated by their sensitivity towards solvent, pH change, redox reaction, Lewis base and counterion, which marks them as potentially useful compounds for optoelectronic applications.

For further details on Nguyen’s group research, visit http://tvnguyengroup.wordpress.com/


 

Project Title: Exploring (anti)aromaticity in large macrocyclic molecules

Supervisor(s): Dr Martin Peeks

Description: You’ve probably heard of Hückel’s rules, which tell us that molecules with [4n+2] pi-electrons are aromatic, and those with [4n] are antiaromatic. But this isn’t always true. Large macrocycles which comprise lots of aromatic subunits seem not to establish global aromaticity, instead ‘preferring’ to maintain the local aromaticity of each subunit. Past examples show that oxidation or reduction of the macrocycle is required to promote a global (anti)aromatic ring current,1 but we want to see whether we can make large molecules which are (anti)aromatic in their neutral oxidation states. Large (anti)aromatic molecules are interesting for two reasons: (1) their existence contradicts the received wisdom of textbooks; and (2) the aromatic ring current, which we observe in NMR chemical shifts of aromatic compounds, appears similar to the persistent current in small (~100 nm) metal rings:2 we need to make bigger (anti)aromatic molecules to see how far the similarities extend, including towards interesting physics in large magnetic fields.
This project spans synthesis, analytical chemistry (NMR, optical spectroscopies), and computational chemistry (DFT analyses of aromaticity).
1. M. D. Peeks, T. D. W. Claridge, H. L. Anderson Nature 2017, 541, 200; M. D. Peeks et al. J. Phys. Chem. Lett. 2019, 2017; N. Toriumi et al. JACS 2015, 82;  2. A. C. Bleszynski-Jayich et al. Science 2009, 326, 272;


 

Project Title: Computational chemistry and biomolecular simulations

Supervisor(s): Dr Junming Ho

Description: In the Mechanisms and Modelling group (MMG), we develop and use quantum chemical calculations and molecular dynamics simulations as a computational microscope to glimpse into the mechanisms of important chemical and biological processes. These insights can help guide experiments, and also lead to the design of more efficient catalysts and effective drug molecules.  If you like to find out more about what computational chemistry can do (or cannot do!), we invite you to join us this summer to work on several of our exciting ongoing projects:

•    Developing novel hybrid quantum mechanics/molecular mechanics (QM/MM) methods for condensed phase simulations
•    Computational design of novel organocatalysts
•    Using machine learning methods to accelerate the discovery of novel drug molecules and catalysts
•    Molecular dynamics simulations of drug interactions with lipid membranes

No background in computational chemistry is assumed as training will be provided. We welcome informal enquiries from prospective students. Please visit the group website (http://www.chemistry.unsw.edu.au/ho-group) for more details on our current research activities.


 

Project Title: Metal complexes of Glyphosate and AMPA analysed by combinatorial mass spectrometry

upervisor(s): Dr Nicole Rijs

Description: N-(phosphonomethyl)glycine, commonly known as Glyphosate, is a ubiquitous herbicide worldwide. Aminomethylphosphonic acid (AMPA) is the main metabolic product of glyphosate. Metal complexation of this herbicide and its degradation product is an important factor affecting the environmental fate in soil and water. Additionally, AMPA is a weak inhibitor of metalloenzymes e.g. leucine aminopeptidase (a Zn2+-containing metalloenzyme), AMPA’s biological activity being linked to its metal complexation properties. In this project, a combinatorial approach based on robotic nanoelectrospray ionisation mass spectrometry (nESI-MS) will be used to determine the metal binding properties of these two species.
Aims:
•    To utilise combinatorial mass spectrometry to screen a matrix of glyphosate or AMPA, metal salt, and solution conditions (concentration, pH, solvent).
•    To qualitatively determine which metal complexes (and clusters) are formed with Glyphosate and AMPA and a series of mono- and dicationic metal salts, via nESI-MS.
•    (time permitting) To determine binding strengths of key complexes using the approach of Pickett et al.


 

Project Title: Magnetic Nanoparticles for Biomedical Applications

Supervisor(s): Prof Richard Tilley

Description: Magnetic nanoparticles are currently the subject of intense research worldwide and hold a strong interest in the field of nanoscience for their numerous applications including contrast enhancement in magnetic particle imaging (MPI), magnetic hyperthermia, and drug delivery. These applications can be improved by using materials that have large magnetisations, such as iron, however strict control on nanoparticle size needs to be achieved, in order to obtain magnetic nanoparticles that are superparamagnetic. Previous work in the group has focused on the development of strongly magnetic single-crystal core/shell iron/iron oxide nanoparticles without the use of highly toxic chemicals, enabling unambiguous detection of small tumours using MPI.

This project will investigate magnetic nanoparticles as new and more effective MPI tracer and hyperthermia agents for the treatment of diseases, in particular cancer. Experience in a variety of techniques will be gained, including nanoparticle solution synthesis and morphology characterisation using UNSW’s state-of-the-art electron microscopy unit.


 

Project Title: Mechanistic and Physical Organic Chemistry

Supervisor(s): A/Prof Jason Harper

Description: Our research falls broadly into the category of physical organic chemistry. However, the areas covered also include biological, bioorganic, synthetic, analytical and environmental chemistry and this demonstrates the range of areas that physical organic chemistry is applicable to. The breadth of topics also illustrates the interdisciplinary nature of the research and the significant scope for collaboration with groups in the more traditional areas of organic chemistry and biochemistry.  We particularly focus on understanding organic processes in ionic liquids, determining reaction mechanisms and developing novel ways to follow reaction progress.
For more details see area see http://www.chem.unsw.edu.au/staffprofiles/harper.html

Materials Science & Engineering

Project Title: Growth and characterisation of ferroelectric heterostructures with topological properties

Supervisor(s): Prof Nagarajan Valanoor

Description: This project involves the use of Pulsed Deposition Method to fabricate nanoscale bubble domains in ultrathin ferroelectric films. The bubble domains are so called “topological defects”- they posses unique polarisation rotation capabilities. The student is expected to fabricate a series of such samples using established synthesis conditions.

The student will then characterize the samples using X-Ray diffraction and Scanning Probe Microscopy. Prior experience with vacuum equipment is an added advantage.

Mathematics and Statistics

Project Title: Curved models for degree distribution

Supervisor(s): Pavel Krivitsky

Description:

Description: Modelling and prediction of networks---relationships among entities---has applications in sociology, epidemiology, and international trade and relations alike. These relationships can interact in complex ways (like a friend of a friend being a likely friend), resulting in dependent observations, and they are not limited to being binary states (like friend versus not-friend) either. A popular framework for complex network models is exponential-family random graph models (ERGMs), which flexibly represent both dependence among relationships and effects of exogenous factors. They have recently been extended to valued network data such as counts of interactions (e.g., how many times have you talked?), rankings (e.g., who is your best, second best, etc. friend?), and signs (e.g., who are your friends, and who are your enemies?). Networks might also evolve over time, and models for evolution of networks have been developed as well. One problem often encountered in social network modelling is that of modelling degree distribution---the distribution of the number of connections each actor has. At its baseline, an ERGM induces a binomial-like distribution, but it is often the case that the distributions are overdispersed relative to that. A possible approach to modelling non-binomial distributions is by giving each degree value a parameter, allowing a very flexible specification; but the devil is in the details.

This project is a continuation of a 2018 Summer project to develop and study specification for non-binomial degree distributions.


 

Project Title: Using penalised likelihood in ERGMs

Supervisor(s): Pavel Krivitsky

Description:

Modelling and prediction of networks---relationships among entities---has applications in sociology, epidemiology, and international trade and relations alike. These relationships can interact in complex ways (like a friend of a friend being a likely friend), resulting in dependent observations, and they are not limited to being binary states (like friend versus not-friend) either.

A popular framework for complex network models is exponential-family random graph models (ERGMs), which flexibly represent both dependence among relationships and effects of exogenous factors. They have recently been extended to valued network data such as counts of interactions (e.g., how many times have you talked?), rankings (e.g., who is your best, second best, etc. friend?), and signs (e.g., who are your friends, and who are your enemies?). Networks might also evolve over time, and models for evolution of networks have been developed as well.

Penalised likelihood can be used to better fit poorly identified models (where there are too many parameters for the amount of data), and can serve as a sort of a ""poor man's Bayes"": it lets one obtain a posterior mode relatively cheaply. This project is to study application of different penalty functions---Ridge, Lasso, and Jeffrys---to ERGMs.

1.  Read background literature and meet with the supervisor to learn about ERGMs and penalised likelihoods.

2.  Use an experimental version of the `R` `ergm` package to test a variety of penalties, perhaps implementing additional ones.

3.  Use real-world datasets and simulation to determine how different likelihood penalties affect ERGM estimation.

 


 

Project Title:  Adaptive MCMC: When to Stop?

Supervisor(s):  Pavel Krivitsky

Description: 

Modelling and prediction of networks---relationships among entities---has applications in sociology, epidemiology, and international trade and relations alike. These relationships can interact in complex ways (like a friend of a friend being a likely friend), resulting in dependent observations, and they are not limited to being binary states (like friend versus not-friend) either.

A popular framework for complex network models is exponential-family random graph models (ERGMs), which flexibly represent both dependence among relationships and effects of exogenous factors. They have recently been extended to valued network data such as counts of interactions (e.g., how many times have you talked?), rankings (e.g., who is your best, second best, etc. friend?), and signs (e.g., who are your friends, and who are your enemies?). Networks might also evolve over time, and models for evolution of networks have been developed as well.

Markov-Chain Monte Carlo (MCMC) methods are widely used in statistical inference, particularly in Bayesian inference. In Bayesian inference, the output of MCMC is examined and summarised by the user to produce intervals and other summaries. However, in other applications, such as Monte-Carlo Maximum Likelihood Estimation (MCMLE) of ERGMs, an MCMC sample is but an intermediate result. Therefore, there is significant interest in automatic ways for determining how long to run the MCMC, and how many of the draws to keep.

At the same time, automatic ways can introduce biases in the estimates of uncertainty due to the use of MCMC. The project will study different automatic techniques for tuning MCMC, implement them, and test them against each other, particularly how they apply to ERGMs and to quantifying uncertainty.

The tentative plan for the project is as follows:

1.  Read background literature and meet with the supervisor to learn about MCMC practices and the concepts behind analysing MCMC output, including autocorrelations, and effective sample sizes.

2.  Review the literature on automatic MCMC stopping criteria.

3.  By working though tutorials and discussion with the supervisor, learn how this is done in the `ergm` package.

4.  Run simulation studies comparing the different stopping criteria on speed, reliability, accuracy, and other criteria.


 

Project Title: Using Maximum Pseudolikelihood Estimation for Model Selection

Supervisor(s):  Pavel Krivitsky

Description:

Modelling and prediction of networks---relationships among entities---has applications in sociology, epidemiology, and international trade and relations alike. These relationships can interact in complex ways (like a friend of a friend being a likely friend), resulting in dependent observations, and they are not limited to being binary states (like friend versus not-friend) either.

A popular framework for complex network models is exponential-family random graph models (ERGMs), which flexibly represent both dependence among relationships and effects of exogenous factors. They have recently been extended to valued network data such as counts of interactions (e.g., how many times have you talked?), rankings (e.g., who is your best, second best, etc. friend?), and signs (e.g., who are your friends, and who are your enemies?). Networks might also evolve over time, and models for evolution of networks have been developed as well.

Maximum Pseudolikelihood Estimation (MPLE) provides fast but inaccurate parameter estimates for ERGMs. Monte Carlo Maximum Likelihood Estimation (MCMLE) is slow but accurate. Model selection requires fitting a large number of models in a rapid succession. Thus, the question is whether MPLE is good for model selection.

The tentative plan for the project is as follows:

1.  Read background literature and meet with the supervisor to learn about ERGMs, MPLE, and model selection.

2.  Review the literature on using composite likelihoods for model selection.

3.  Perform simulation studies to determine,

    -   how well MPLE-based model selection captures what MLE would have selected. -   how well do the different selection methods recover the truth.

 


 

Project Title: Who is Heard at a Business Meeting? Understanding Social Forces at a Law Firm

Supervisor(s): Pavel Krivitsky

Description:

In 1988--1991, Emmanuel Lazega and his team undertook a detailed study of a corporate law firm in Northeastern United States. A great deal of data were collected about each of the 71 attorneys at the firm---partners and associates---and their interactions. The data include their seniority, gender, and area of practice. Perhaps more interestingly, Lazega also collected relational data, who has received advice from whom, and who has received help in preparing briefs and legal reviews; as well as who considers whom a personal friend. These data have formed the basis of dozens of studies and analyses. In addition, Lazega asked each of the partners in the firm---the attorneys who "own" the firm and make the important decisions---what other partners' opinions they valued at business meetings. This aspect of the data is less explored.
This project will use cutting-age network modelling techniques developed by the supervisor to obtain new insights about the social forces driving collaboration, competition, and influence in a corporate environment. Emphasis will be placed on interactions of partners, as well as how partner interactions influence other types and are influenced by them.
The tentative plan for the project is as follows:

1.  Read background literature and meet with the supervisor to learn about social network analysis, particularly Exponential-Family Random Graph Models (ERGMs).
2.  Work through tutorials to learn the `ergm` `R` package for estimating ERGMs.
3.  Through discussion with the supervisor and (occasionally) Emmanuel Lazega, develop hypotheses about partner-partner interactions and models to test them.
4.  Write an article reporting the results.
In 1988--1991, Emmanuel Lazega and his team undertook a detailed study
of a corporate law firm in Northeastern United States. A great deal of
data were collected about each of the 71 attorneys at the
firm---partners and associates---and their interactions. The data
include their seniority, gender, and area of practice. Perhaps more
interestingly, Lazega also collected relational data, who has received
advice from whom, and who has received help in preparing briefs and
legal reviews; as well as who considers whom a personal friend. These
data have formed the basis of dozens of studies and analyses. In
addition, Lazega asked each of the partners in the firm---the attorneys
who "own" the firm and make the important decisions---what other
partners' opinions they valued at business meetings. This aspect of the
data is less explored.
This project will use cutting-age network modelling techniques developed
by the supervisor to obtain new insights about the social forces driving
collaboration, competition, and influence in a corporate environment.
Emphasis will be placed on interactions of partners, as well as how
partner interactions influence other types and are influenced by them.

The tentative plan for the project is as follows:

1.  Read background literature and meet with the supervisor to learn
    about social network analysis, particularly Exponential-Family
    Random Graph Models (ERGMs).
2.  Work through tutorials to learn the `ergm` `R` package for
    estimating ERGMs.
3.  Through discussion with the supervisor and (occasionally) Emmanuel
    Lazega, develop hypotheses about partner-partner interactions and
    models to test them.
4.  Write an article reporting the results

 


 

Project Title: The potential vorticity of salt water and moist air

Supervisor(s):  Geoff Stanley, Trevor McDougall

Description: Since the 1940's, the key concept in large-scale atmospheric and oceanic dynamics is that of potential vorticity (PV).  As a single scalar field, PV captures both dynamics and thermodynamics by combining three fundamental conservation laws -- those for mass, momentum, and potential enthalpy -- into one all-encompassing conservation law.  The original 1942 definition of PV is valid only for single-component fluids such as dry air or fresh water, where the density is determined purely from the temperature and pressure.  Unfortunately, variations of moisture in the atmosphere and variations of salinity in the ocean break the PV conservation law.  Various definitions have been proposed for moist air PV and salt water PV, each associated with an approximate conservation law of varying quality.  This project defines a new PV that naturally generalizes the 1942 PV to multicomponent fluids such as these.  We will assess the quality of its conservation law in both oceanographic and atmospheric datasets, comparing against those for previous definitions of PV.

 


 

Project Title: Pushing the ocean to extremes

Supervisor(s): Ryan Holmes, Jan Zika

Description: What would happen if we suddenly warmed the entire ocean at the sea-surface? Would suddenly cooling it down cause an equal and opposite response? Using state-of-the-art ocean climate models we have carried out these and many more extreme experiments. We now seek a summer student to help understand the asymmetric and often surprising behaviour of the ocean in response. The student will work towards developing novel theories to describe the ocean. These theories are needed to understand the ocean's role in transient climate change.

Note: Ryan Holmes' affiliation is CCRC/School of Mathematics and Statistics


 

Project Title: Distilling the ocean’s role in climate using phase diagrams and machine learning

Supervisor(s): Ryan Holmes, Jan Zika

Description: Understanding how much and to what depth heat will be pumped into the ocean is critical to predict future surface temperature and sea-level rise. This study will investigate vertical heat transport in the ocean using novel thermodynamic diagrams. Using such diagrams, which have origins in classical thermodynamics, one can relate the circulation to surface heating and cooling processes and mixing. The diagrams also lend themselves to the application of novel image processing/unsupervised machine learning techniques. The student will make use of the most recent observations and combine these novel machine learning and image processing techniques to understand the drivers of recent ocean change.

Note: Ryan Holmes' affiliation is CCRC/School of Mathematics and Statistics


 

Project Title: Dynamics of a marine heatwave off Tasmania: what happens below the surface?

Supervisor(s): Amandine Schaeffer

Description: Extreme temperatures in the ocean are getting more frequent and intense, impacting marine ecosystems and industries. However the subsurface signature of these marine heatwaves is still largely unknown, in particular in shallow coastal areas where most of the ecological damages occur.
In addition to sustained observations, the Australian Integrated Marine Observing System (IMOS) now aims at sampling the coastal ocean during marine heatwaves with targeted deployments of ocean gliders. Gliders are automated underwater vehicles which measure the water properties between the ocean floor and the surface for a few weeks. Two of such deployments were successfully finalised, sampling the eastern shelf of Tasmania during the latest marine heatwave event in the Tasman Sea lasting a few months.
The project will be in collaboration with the University of Tasmania and aims at understanding the extent and characteristics of the marine heatwave using the glider measurements and complementary satellite of moored observations. Key questions include the temporal evolution, from the onset to the decline of the extreme event, and the influence of local oceanography such as currents and wind-driven processes on its persistence and variability.
Basic knowledge of oceanography and experience in Matlab or Python are required.

 


 

Project Title: Dimensions of convex faces

Supervisor(s): Vera Roshchina

Description: Convex sets are fundamental objects in mathematics, and are in particular useful for modelling and solving optimisation problems, where they usually feature as constraints. The (boundary) structure of convex sets can be studied by means of their faces, which generalise vertices, edges and facets of polyhedral sets.In finite-dimensional real vector spaces every face of a convex set has an integer dimension associated with it. We know that in general faces of convex sets can come in any combination of dimensions. The goal of this project is to verify (or disprove) that a similar result is true for restricted classes of convex sets, such as facially exposed sets and spectrahedra. For more details, images and references please visit this project description page: https://www.roshchina.com/projects/dim-faces/.

 


 

Project Title: Description of optimal generators in a homology group. Implementation in R software and applications.

Supervisor(s): Dr Mircea Voineagu 

Description: Computation of equivariant invariants for an equivariant topological space. In particular, computation of Bredon cohomology of a point with trivial Z/2xZ/2-action.

 


 

Project Title:  Computation of equivariant invariants for an equivariant topological space. In particular, computation of Bredon cohomology of a point with trivial Z/2xZ/2-action.

Supervisor(s): Dr Mircea Voineagu 

Description: We study in detail the ground breaking paper of Quillen about the definition of algebraic K-theory. Application in the direct computations of some schemes or rings.

 

Optometry & Vision Science

Project Title: Drug Delivery from Contact Lenses

Supervisor(s): Dr Alex Hui

Description: This project will investigate the application of contact lenses for drug delivery properties. The ability of available contact lens materials will be evaluated for drug uptake and release properties in the laboratory and novel methods to manipulate these drug-material interactions will be explored.


 

Project Title: Evaluation of the effect of an aqueous free, preservative free eye drop on tear film properties.

Supervisor(s): Dr Maria Markoulli & Dr Jacqueline Tan

Description: A randomised, non-dispensing study to evaluate the effect of NovaTears® on tear film characteristics, compared to Hylo-Forte® and preservative-free unit dose saline, up to one hour post-instillation.


 

Project Title: Knowledge, Attitude, and Practices of people with Macular Degeneration

Supervisor(s): A/Prof Isabelle Jalbert

Description: This project aims to explore knowledge, attitudes and practices (KAP) of people with macular degeneration in Australia. This project has received ethics approval. A pre-designed KAP survey will be administered to a sample of people with macular degeneration in Australia using paper-based (reply post mailout) scannable questionnaires. The student will be expected to proactively participate in the recruitement of people with macular degeneration. Total and individual domain KAP scores will be summarised using descriptive statistics. Multivariable logistic regression analysis will be performed to assess the effect of factors such as age, gender, location, macular degeneration stage, etc., on the overall and sub-domain KAP scores of people with macular degeneration. The student will be involved in data entry, data analysis and interpretation of the research findings.


 

Project Title: Looking at the melanocytes between the choroid and sclera: can we see patterns in the lamina fusca?

Supervisor(s): A/Prof Michele Madigan

Description: In the eye, the choroid, ciliary body and iris form a vascular pigmented uveal layer between the outer sclera and the inner eye tissues. In these tissues, the pigmentation comes from the melanocytes, an abundant heterogeneous melanin-containing population within these tissues. Melanocytes are especially obvious at the interface between the choroid and sclera, and clearly seen when the choroid is dissected away from the sclera of the eyecup. We will examine the scleral interface of formalin-fixed human eye cups to investigate the organisation and patterns of melanocytes at the lamina fusca, particularly related to the blood vessels and nerves in this area. This will involve using digital imaging and image analysis. The project will provide hands-on experience in human eye gross anatomy (dissecting, macrophotography, and imaging), and microscopy. A greater appreciation of human eye anatomy and cell biology is a further aim of this project.


 

Project Title: Freckles and naevi in the adult human iris.

Supervisor(s): A/Prof Michele Madigan

Description: Melanocytes are the pigmented cells of the uveal tract (iris, ciliary body and choroid), and accumulate to form freckles and naevi. Some may transform to iris and choroid melanoma. Information about the distribution of melanocytes and their relationship to freckles and naevi in normal adult human iris is limited. We will survey and digitally image post-mortem human iris tissue. This will involve iris colour grading using digital imaging techniques developed by SOVS students in 2017. This is a hands-on project providing experience in human eye gross anatomy (dissecting and macrophotography), and some laboratory techniques including immunohistochemistry and light and confocal microscopy. An enhanced appreciation of human eye anatomy and cell biology is a further aim of this project.


 

Project Title: Project Title: Modelling the economic cost of severe corneal infections.

Supervisor(s): Dr Nicole Carnt, Prof Lisa Keay, Dr Nina Tahhan

Description: Acanthamoeba causes a rare but severe corneal infection in mainly contact lens wearers. These patients tend to be of working age and with otherwise good health. Our research has shown that 50% of these patients have treatment for more than 12 months and 1 in 5 require a corneal transplant. Worryingly, an increasing number of children are being prescribed contact lenses to correct and retard myopia. In this study, you will use a large data set of clinical and quality of life data on patients with Acanthamoeba corneal infection to demonstrate the economic cost and lifetime burden of this severe disease. This will hopefully provide impetus for contact lens practitioners, industry and regulators to invest in strategies to mitigate this disease.


 

Project Title: An ex-vivo model of Primary Herpes Simplex Keratitis

Supervisor(s):  Dr Nicole Carnt, Dr Damien Hunter, A/Prof Andrew Harmen

Description: Herpes Simplex Keratitis is a chronic, relapsing infection of the clear, refracting surface of the eye, the cornea. To maintain the regular structure of the cornea for precise vision, it is devoid of blood vessels. Only in recent years has a population of tissue resident antigen presenting cells (APCs) been identified in the cornea. The roles of these APCs, how they interact with inflammation, the immune system and other cells in the cornea in patients is not well understood. In this project, you will use an explant model of Herpes Simplex corneal infection to determine the tissue response to primary infection, using techniques such as immunofluorescence histology, flow cytometry and protein analysis. In this collaboration between the School of Optometry and Vision Science, UNSW, Centre for Virus Research and Centre for Vision Research at Westmead Institute for Medical Research, you will work with world leading experts in Herpes virus and eye infection research.


 

Project Title: Project Title: Investigating corneal limbal stem cell dysfunction in contact lens wearers

Supervisor(s): Dr Nicole Carnt

Description: Contact lens (CL) wear has been recently recognised as a cause of failure of the stem cells of the eye’s surface. Poor vision and ocular discomfort follow ocular surface (limbal) stem cell failure. This project is one of the first to examine contact lens wearers for dysfunction of limbal stem cells or damage to their specialised ‘niche’ environment. With the increasing prevalence of contact lens wear and the use of contact lenses for stem cell replacement therapies, investigation of stem cell damage with contact lens wear has the potential to save sight, improve contact lens design and optimise stem cell replacement therapies. In this study, we aim to assess a group of CL wearers in parallel with a group of non-lens wearing healthy ‘negative’ controls to investigate changes that may suggest limbal stem cell dysfunction. Specialised imaging techniques will be used, and anatomical patterns will be compared to the reported signs in established limbal stem cell deficiency.


 

Project Title: Project Title: Can artificial intelligence accelerate the diagnosis process of glaucoma?

Supervisor(s): Dr Maitreyee Roy

Description: With the increasing prevalence of ocular diseases like glaucoma, diabetic retinopathy and age-related macular degeneration; annual screening for ocular diseases by a human expert, grading of retinal images is challenging. Automated retinal image assessment systems (ARIAS) may provide clinically effective and cost-effective detection of ocular diseases. Recently, machine learning approaches have become increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This research project will highlight new research directions and examine the main challenges related to machine learning in ocular imaging, applying novel deep learning algorithms to automatic analysis of both digital fundus photographs and OCT images from both healthy control subjects and patients undergoing treatment for relevant ocular diseases. On top of existing clinical markers of disease, this project will have a focus on developing novel metrics for distinguishing between glaucomatous and non-glaucomatous eyes.


 

 

Physics

Project Title: Photonics and Optoelectronics

Supervisor(s): Reece,Peter John

Description: https://www.physics.unsw.edu.au/research/condensed-matter-physics/projec...


 

Project Title: Astrophysics and Astrochemistry

Supervisor(s): Cunningham,Maria

Description:  https://www.physics.unsw.edu.au/research/astrophysics/projects/maria-cun...


 

Project Title: Exoplanets and Brown Dwarfs

Supervisor(s): Tinney,Christopher Geoffrey

Description: https://www.physics.unsw.edu.au/research/astrophysics/projects/chris-tin...


 

Project Title: Optical Spectroscopy and neutron scattering

Supervisor(s): Ulrich,Clemens

Description: https://www.physics.unsw.edu.au/research/condensed-matter-physics/projec...


 

Project Title: Sounding stars using data from NASA's kepler and TESS missions

Supervisor(s): Stello,Dennis

Description: https://www.physics.unsw.edu.au/research/astrophysics/projects/dennis-st...


 

Project Title: Quantum computation in silicon

Supervisor(s): Rogge,Sven

Description: https://www.physics.unsw.edu.au/research/condensed-matter-physics/projec...


 

 

Project Title: Galaxy Evolution across cosmic time

Supervisor(s): Tran,Kim-Vy Huu

Description: https://www.physics.unsw.edu.au/research/astrophysics/projects/kim-vy-tr...


 

Project Title: Astronomy from Antarctica

Supervisor(s):  Ashley,Michael Charles Brewster

Description: https://www.physics.unsw.edu.au/research/astrophysics/projects/michael-a...


 

Project Title: Biophysics

Supervisor(s): Curmi,Paul Marie Gerard

Description: https://www.physics.unsw.edu.au/research/biophysics/projects/paul-curmis...

 


 

Project Title: Theoretical Physics

Supervisor(s): Flambaum,Victor

Description: https://www.physics.unsw.edu.au/research/theoretical-physics/projects/vi...

 


 

 

Project Title: Fabry Perot interferometer with Quantum Point Contact

Supervisor(s): Sushkov,Oleg P

Description: https://www.physics.unsw.edu.au/research/theoretical-physics/projects/fa...

 


 

 

Project Title: Theoretical Physics

Supervisor(s): Berengut,Julian Carlo

Description: https://www.physics.unsw.edu.au/research/theoretical-physics/projects/ju...


 

 

Project Title: Centre for Quantum Computation and Communication Technology

Supervisor(s): Simmons,Michelle Yvonne

Description: https://www.physics.unsw.edu.au/research/condensed-matter-physics/projec...

 


 

 

Project Title: Experimental Condensed Matter Physics

Supervisor(s): Hamilton,Alexander

Description: https://www.physics.unsw.edu.au/research/condensed-matter-physics/projec...

 


 

 

Project Title: Excitonic Materials and Devices

Supervisor(s): McCamey,Dane Robert

Description: https://www.physics.unsw.edu.au/research/condensed-matter-physics/projec...

 


 

Project Title: Galactic Archaeology

Supervisor(s): Martell, Sarah

Description: https://www.physics.unsw.edu.au/research/astrophysics/projects/sarah-mar...


 

 

Psychology

Project Title: Neurobiology of addiction

Supervisor(s): Dr Kelly Clemens

Description: Drugs of abuse lead to lasting epigenetic changes in gene expression: genes can be switched on or off by exposure to drugs. This project examines what impact this might have for the development of addiction and its relapse, as well as isolating the types of changes that occur.


Project Title: Emotions: approach-motivated negative emotions and positive high-approach emotions

Supervisor(s): Prof Eddie Harmon-Jones

Description: My lab studies emotions, particularly approach-motivated negative emotions such as anger and sadness, and positive high-approach emotions such as desire and determination. We also research other motivational processes such as cognitive dissonance. In general, we are interested in investigating the influence of emotional and motivational states on attentional, cognitive, social, and behavioural processes. We use non-invasive human neuroscience methods (e.g., electroencephalography, event-related potentials, startle eyeblink responses, transcranial direct current stimulation), self-report methods, and behavioural methods (e.g., reaction times).


Project Title: Influence of predictive stimuli on choice between actions

Supervisor(s): Dr Vincent Laurent

Description: Successful decision-making requires the ability to extract predictive information from the environment to guide future actions. This ability is commonly modelled in the laboratory through specific Pavlovian-Instrumental transfer. This phenomenon shows that a stimulus predicting a particular food outcome biases choice towards actions earning that same outcome. This bias is present in many species including humans, monkeys, horses, rats and mice but its psychological processes remain largely unknown. This project will explore the conditions under which Pavlovian-Instrumental transfer is expressed and will evaluate how it can be removed.


Project Title: Examining object and scene recognition across variations in illumination and sound source perception across variations in environment and source distance.

Supervisor(s): Dr Damien Mannion

Description: Perception has the task of identifying useful information about the world. This task is often challenging due to the presence of confounding factors in sensory signals. We research how humans approach this challenge in visual, auditory, and multisensory domains. Ongoing projects involve examining object and scene recognition across variations in illumination and sound source perception across variations in environment and source distance.


Project Title: Cell-type specific brain imaging during relapse to drug seeking

Supervisor(s): Prof Gavan McNally

Description: Relapse to drug-taking is the fundamental problem facing any treatment of drug addiction. 70-80% of drug- users seeking treatment will relapse to drug taking within 12 months of treatment. The brain mechanisms of this relapse are poorly understood but this knowledge is needed to generate new treatment platforms. To this end, in this project, students will gain hands on experience with state of the art techniques to image the activity of genetically defined neurons during relapse to drug seeking in awake freely moving animals.


Project Title: Evaluating Experts

Supervisor(s): A/Prof Kristy Martire

Description: Every day experts offer us advice and opinions about a huge variety of decisions. But not all experts are equal. This project examines how people decide which expert to believe and which expert to ignore. I am looking for a student with an interest in decision-making and forensic psychology to assist with research that will help us to understand and improve the way experts are evaluated. The intern will be involved with stimuli development, computer programming, online distribution and monitoring of experiments, and data cleaning and documentation.


 

Project Title: Technology-based interventions and tools for mental health

Supervisor(s): Dr Jill Newby

Description: Online and virtual reality tools are being used to improve wellbeing in the general population and in people who experience anxiety disorders and depression. This project students will directly contribute to ongoing studies in the lab related to technology-based interventions and tools for mental health. The student will be involved with recruiting research participants, developing and testing new online or virtual reality tools, literature reviews, transcribing interviews, data coding, and data analysis.


 

Project Title: Understanding Refugee Trauma and Recovery

Supervisor(s): A/Prof Angela Nickerson

Description: The number of forcibly displaced individuals worldwide is unprecedented. The Refugee Trauma and Recovery Program (RTRP) in the School of Psychology UNSW Sydney is dedicated to understanding the psychological and neurobiological effects of refugee trauma and pathways to recovery. This summer vacation, we are seeking a student intern to assist across various research projects with trauma-exposed refugees. These experimental and online projects aim to identify and understand the factors that influence refugee mental health and psychological well-being during resettlement. Working closely with the RTRP team, the selected intern will assist with conducting experimental sessions and be actively involved in data management, participant retention and engagement.


 

Project Title: Hindbrain control of feeding behaviours

Supervisor(s): Dr Zhi Yi Ong

Description: It is clear that overeating is a key contributor to increased obesity rates. Obese individuals overeat because they are less sensitive to gut signals that are responsible for making one feel full and stop eating. It is therefore critical to understand the gut-brain mechanisms that control feeding behaviours to better guide the development of treatments that can promote long term body weight loss. This project will explore the role of hindbrain neurons that receive inputs from the gut, on the control of feeding behaviours. Using transgenic rodent models, students will have the opportunity to run feeding behavioural tasks and perform histological and microscopy analyses.


 

Project Title: The scientific study of intuition

Supervisor(s): A/Prof Joel Pearson

Description: What is human intuition? How can it be measured and can it be improved? We have devised the first scientific technique to measure intuition. Using this method, we found evidence that people can use intuition to make faster, more accurate and more confident decisions. This groundbreaking discovery is the first to show scientific evidence that intuition actually exists and a new method to objectively measure it. We have ongoing projects using novel empirical paradigms, physiological measures and computational decision models to show that unconscious emotional information can boost accuracy in concurrent emotion-free decision tasks. New projects are available using these techniques to study intuition, its genetic and brain basis and its application. e.g. can we train the military, sports stars or entrepreneurs to be more intuitive or more productive with their intuition?


 

Project Title: Behavioral, pharmacological and molecular biology tools to identify the neural circuitry underlying drug addiction

Supervisor(s): Dr Asheeta Prasad

Description: Drug addiction is a chronically relapsing and complex disorder. This project applies a combination of behavioral, pharmacological and molecular biology tools to identify the neural circuitry underlying drug addiction.


 

Project Title: Better understanding and treatments for Parkinson’s disease

Supervisor(s): Dr Asheeta Prasad

Description: 

Parkinson’s disease (PD) is a neurodegenerative disorder that affects approximately 10 million people globally; with approximately 32 Australians being diagnosed daily. The symptoms of PD are motor (e.g. slowness, stiffness) and non-motor including cognitive impairment, anxiety, and depression. Using optogenetics, this project aims to provide better understanding and treatments for Parkinson’s disease.


 

Project Title: Facial Comparison

Supervisor(s): Dr Alice Towler

Description: 

Important identification procedures, such as identifying offenders from CCTV footage, require facial comparison staff to verify the identity of unfamiliar people by comparing faces. However, unfamiliar face identification is a very challenging and error-prone task. It’s therefore critical that we recruit people for these roles who are naturally skilled at identifying people. We plan to design face recognition tests that capture the types of face recognition decisions encountered by facial comparison staff, such as searching for a person of interest in a football stadium or train station surveillance footage. These tests could be used to recruit facial comparison staff, and increase our understanding of the skills necessary to accurately identify people in these applied scenarios.

 


 

Project Title: Attentional capture by reward

Supervisor(s): Dr Poppy Watson

Description: Cues in the environment that signal the availability of reward become motivational magnets in their own right, capturing attention and motivating reward-seeking behaviours. Sometimes, however, it is in our best interests to ignore these reward signals and it has been argued that the extent to which individuals can do this relates to vulnerability for the development of compulsive reward seeking - as is observed for example in addiction. In our lab we use a variety of techniques and tasks to investigate (involuntary) attentional capture by stimuli signalling reward. We are particularly interested in how attentional capture by reward is increased when participants are stressed or under the influence of alcohol or when rewards become more motivationally salient (through for example testing participants when they are hungry in a task where they can win food rewards).  There are a variety of possible projects along these themes, depending on what the student finds interesting.

 


 

Project Title: Face recognition

Supervisor(s): Dr David White

Description: Many forensic and security procedures use face photographs to verify the identity of unknown people. However, face matching is a surprisingly difficult and error-prone task – on average, people make an error 1 in every 4 or 5 decisions. Recently, researchers have discovered that a small portion of the population have extraordinary face recognition ability. These ‘super-recognisers’ demonstrate almost perfect accuracy, even in very challenging conditions. We recently recruited a large group of super-recognisers to participate in our research. We plan to investigate why they can identify faces so much better than other people, and whether they are also skilled at other tasks, such as recognising members of the same family.


 

Project Title: Effects of early life stress on learning in memory

Supervisor(s): Professor Rick Richardson

Description: Experiencing adversity early in life is a major risk factor for a variety of physical and mental health conditions. This project explores some of the effects, behaviourally and/or neurally, of early life stress on learning and memory processes in the rat.

 


 

Project Title: Neuroanatomical analysis of emotion regulation across development

Supervisor(s): Professor Rick Richardson

Description: Recent work has indicated that the neural mechanisms underlying both the expression and the inhibition of learned fear change across development. This project continues to explore these developmental differences with the goal of improving our understanding of emotional regulation across the lifespan.


 

Project Title: Neural mechanisms underlying the effects of chronic stress exposure in adolescence on fear regulation

Supervisor(s): Dr Kathryn Baker

Description: Adolescence is a stress-sensitive stage of development and a time when anxiety disorders often emerge. Chronic exposure to stress hormones during adolescence is known to impair the regulation of fear regulation. Students will be involved in an ongoing project exploring the neural mechanisms underpinning how chronic exposure to the stress hormone corticosterone impairs fear inhibition in adolescent rats.