UNSW Science Vacation Research Scholarship UGVC1056
2023/ 2024 Research Projects

The purpose of the UNSW Science Summer Vacation Research Scholarship program is to expose 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 must submit the following:

Supporting Documentation

Please submit the following with your Scholarship application (Part 1):

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

Applications are now open and will close Friday 15 September 2023.

Research Projects

Click on the Schools below to view possible research projects:

School of Biotechnology and Biomolecular Sciences Projects

Project Title: Understanding the function of cis-regulatory elements

Supervisor(s): A/Prof Emily Wong

Description: The project will involve assisting with and learning high throughput assays and cell culture.

Experience: Molecular biology / genetics background.

Project Title: Understanding the regulatory genome

Supervisor(s): A/Prof Emily Wong

Description: The project will involve assisting with data analysis in bulk / single cell or machine learning.

Experience: Computational experience.

School of Physics Projects

Project Title: Sighting the Spotted Surfaces of Sun-like Stars

Supervisor(s): Dr Ben Montet

Description: Observations of the growth, decay, and locations of sunspots provide clues about the nature of the Sun's magnetic field. To understand the potential habitability of exoplanet systems, we want to understand the ways in which their host stars' magnetic fields are different from our own Sun's. One way to accomplish this is through observations of starspots. In this project, we will use exoplanet transits, the moments when a planet crosses the surface of its host star, casting a shadow along one stellar chord, to infer the distributions of starspots on stars of different ages, masses, and compositions. These data will enable us to characterise how these parameters affect stellar magnetic fields. This project will involve programming in Python; prior programming experience in any language will be helpful but not required.

Experience: None

Project Title: Atomically thin van-der Waals materials

Supervisor(s): Dr Feixiang Xiang & Prof Alex Hamilton

Description:Graphene, a single layer of carbon atoms with honeycomb lattice structure, shows many exotic physics and promising properties for device applications. Stacking different layers together provides a degree of freedom to change electronic properties of graphene, such as electronic band structures. In this summer project, the successful applicant will work with a team from QED group from School of Phyiscs at UNSW to explore effect of different stacking order on electronic properties of ABA- and ABC- stacked trilayer graphene. The successful applicant will participate in fabrication of van der Waals heterostructure and measuring their electronic properties in an environment of ultracold temperatures and high magnetic fields.

Experience: Suited to students wanting to do hands-on lab work.

Project Title: Hole spins in strained Germanium 

Supervisor(s): Dr Matthew Rendell & Prof Alex Hamilton

Description: Despite being used in the first transistor, Germanium was replaced by Silicon in most semiconductor devices. Recently, strained Germanium has had a resurgence in nanoscale electronics due to its interesting quantum properties including spin-orbit interactions and coupling to superconductors. These properties make strained Germanium useful for quantum computing using spin qubits, low energy topological electronics, and exotic superconducting states. In this project you will have hands on lab experience measuring the quantum properties of holes in strained Germanium electronic devices using cryogenic systems and low noise measurement techniques.

Experience: Suited to students wanting to do hands-on lab work.

Project Title: Hole spins for quantum information

Supervisor(s): Dr Scott Liles & Prof Alex Hamilton

Description: The understanding of the quantum mechanical properties of positively charged holes in nanoscale electronic devices is far from complete, despite the fact that your mobile phone contains billions of transistors that use holes. This is because although undergraduates are often taught that valence band holes are essentially just heavy electrons, with a positive charge and a positive effective mass, holes are spin-3/2 particles whereas electrons are spin-1/2. The spin-3/2 nature of holes means they make excellent spin quantum bits, and this project will involve hands on laboratory research to develop new research tools to study how to read and manipulate hole spin qubits. See http://www.phys.unsw.edu.au/QED for more details.

Experience: Suited to students wanting to do hands-on lab work.

Project Title: Measuring the quantum capacitance

Supervisor(s): Dr Joe Hillier & Prof Alex Hamilton

Description: Classical capacitance is a purely geometrical effect. The quantum capacitance results from the discrete energy levels of electrons in solids, and provides unique insights into the electronic properties of quantum devices (even if they are insulating). This project will design and test new experimental setups for measuring the quantum capacitance at ultra-low temperatures in advanced semiconductor devices.

Experience: Suited to students wanting to do hands-on lab work.

Project Title: Quantum Hall Effect

Supervisor(s): Dr Daisy Wang & Prof Alex Hamilton

Description: In the classical Hall effect, a current flowing through a conductor placed gives rises to a transverse Hall voltage that depends linearly on the applied magnetic field. The 1985 Nobel Prize in Physics was awarded for the totally unexpected discovery that the Hall resistance in thin two-dimensional conducting sheets in silicon transistors is not linear, but jumps in steps, and depends only on the electron charge and Planck's constant. In 1988 another Nobel Prize was awarded for the unexpected discovery of the fractional quantum Hall effect, which seemed to indicate electrons were breaking up into fractionally charged objects. This project will measure quantum Hall effect in two-dimensional transistors at temperatures below 2 Kelvin and magnetic fields up to 9 Tesla, use this information to improve the device and experiment design.

Experience: Suited to students wanting to do hands-on lab work

Project Title: Magnetohydrodynamic flow of electrical current

Supervisor(s): Dr Yonatan Ashlea Alava & Prof Alex Hamilton

Description: We often talk of electrical current as the flow of a fluid of electrons. But fluids have viscosity and turbulence - does this happen in electrical current too?

Experience: Suited to students wanting to do hands-on lab work

Project Title: An electron traffic jam - hydrodynamic flow of electrical current

Supervisor(s): Dr Matt Rendell & Prof Alex Hamilton

Description: We often talk of electrical current as the flow of a fluid of electrons. But fluids have viscosity and turbulence - does this happen in electrical current too?

Experience: Suited to students wanting to do hands-on lab work

Project Title: New spin qubit implementations using levitating electrons

Supervisor(s): Dr Maja Cassidy

Description: Electrons levitating on the surface of noble gases are a promising system for implementing spin qubits in a defect-free environment. This short project will focus on designing, manufacturing and testing the system required for freezing neon on the surface of a superconducting resonator inside a dilution refrigerator, and developing the electron trap architecture for implementing the first neon based spin qubits. You will learn experimental techniques in microwave device characterization and cryogenics, as well as data analysis. 

Experience: None

School of Psychology Projects

Project Title: Face categorisation in super-recognisers

Supervisor(s): A/Prof David White & Dr James Dunn

Description: People naturally categorise faces according to gender, ethnicity, expression and identity.  The UNSW Face Research Lab have identified a group of ’super-recognisers’ with extremely high ability to recognise the identity of faces, but little is known about their abilities in categorising faces according to aspects other than identity.  In this project the student will help to implement an experiment that tests super-recogniser’s ability to make speeded face categorisation judgments of gender, ethnicity, expression and facial first impressions (e.g. trustworthy V untrustworthy).  By knowing whether super-recognisers are quicker to make these categorisations, we hope to develop a better understanding of super-recognisers superior face processing abilities.  Results will also help to better understand why people form social categories — e.g. between different ethnic groups — that can bias the outcomes of real-world decisions, for example in legal and everyday social settings. 

Experience: None

Project Title: Pathways to maladaptive decision-making

Supervisor(s): Prof Gavan McNally

Description: This project studies the different ways in which decision-making processes may be corrupted and contribute to maladaptive choices. It uses human, rat, and mouse models of choice to study the core psychological and brain mechanisms of choosing to pursue a reward despite adverse consequences. Depending on their interests, students will be exposed to behavioural training, AI-assisted behavioural phenotyping, computational modelling, in vivo fibre photometry, single and two-colour calcium imaging via head mounted microscopes, single cell spatial transcriptomics, and human behavioural data collection.         

Experience: None

Project Title: Effective Communication of Climate Risk Information

Supervisor(s): Dr Omid Ghasemi & Prof Ben Newell

Description: Climate change is an undeniable reality with profound implications for our daily decision-making. In this project, our focus lies on individuals' choices when purchasing real estate properties that come with varying levels of climate risk. With the rise of websites and organizations providing climate risk assessments for properties, it becomes intriguing to explore how people incorporate this information into their decision-making and identify the psychological factors that influence their risk awareness. Furthermore, this project aims to enhance climate risk awareness by employing well-established psychological techniques. By doing so, we not only gain valuable insights into human judgment processes but also advance our understanding of how to effectively communicate risk information to the public. 

Experience: None required.Some experience with computer programming / data analytics helpful. 

Project Title: SciX 2024 - Mental Health and Cognition

Supervisor(s): Dr Jamie Dracup, A/Prof Steve Most & Dr Laura McKemmish

Description: This project is a chance to get involved with science outreach work this summer. For SciX 2024 a group of high school students will come onto campus for one week, during January. While on campus, these students will carry out an online research project as part of their HSC. This project will look into how mental health impacts the way that we feel and process information. You will help prepare and run this week, and will also carry out literature review and data analysis which will go beyond the more foundational work that the SciX students will do. This more complex work will contribute to publication of data collected during this SciX and in previous online studies. This is a great opportunity to share university level science with HSC students, while building your own skills.

Experience: Some experience with teaching/tutoring, statistical analysis of research data, and scientific literature review would be ideal. Note that this experience is not essential.

Project Title: Underpinnings of punishment avoidance

Supervisor(s): Dr Philip Jean-Richard-dit-Bressel

Description: When our actions have negative consequences, we are usually able to learn about this relationship to avoid making that action again in the future (“punishment learning”). Our research seeks to understand how this learning happens, when and why it fails, and how decisions regarding punishment are resolved, at psychological and neurobiological levels. We investigate these processes using state-of-the-art neuroscience techniques in rodent models as well as specially-designed tasks in humans.

Experience: None

Project Title: The role of attention in colour constancy

Supervisor(s): Dr Erin Goddard

Description: How do our brains separate raw colour information into different sources? The apparent surface colour of objects depends on how we interpret the lighting conditions of the scene (e.g. #theDress), a process known as ‘colour constancy’. To better understand the neural processes involved in these phenomena, this project will test the role of attention in the perceptual separation of different colour sources. The project will involve collecting measurements of perceived colour for human participants using a computer and specialised display. No prior experience is necessary: data collection and analysis will involve working with Matlab and some statistical analyses, but all required skills will be taught as part of the project. In the lab, we also investigate human visual perception using fMRI and magnetoencephalography (MEG), and summer students will have the option of also being involved in these experiments if they are interested.

Experience: None

Project Title: Applying time series analysis / machine learning methods to Magnetoencephalography (MEG) data

Supervisor(s): Dr Erin Goddard & A/Prof Gustavo Batista

Description: Magnetoencephalography (MEG) is a non-invasive human brain recording method where neural responses can be measured while the participant views a stimulus and/or performs a task. This creates rich datasets (e.g. 160 sensors / channels from across the brain, recorded at 1000 Hz). To help gain insights into brain function, machine learning approaches can be useful for measuring the stimulus-related and/or task-related information in the neural signals. This project will involve extending on existing methods by trying out approaches from time series analysis on existing MEG datasets. This project is part of a collaboration between Dr Erin Goddard (Psychology), who uses MEG to address questions of visual neuroscience, and A/Prof Gustavo Batista (Computer Science), who is an expert in machine learning and time series analysis. In this project, the student will work with both Dr Goddard and A/Prof Batista to plan a new approach, write code to execute the analysis, and try it out by applying the approach to existing MEG datasets. This would suit a student with interest and experience in both psychology and computer science and/or machine learning.

Experience: Prior experience in coding in at least one of Matlab or python is required. If you are unsure whether you have enough experience, you are welcome to contact Dr Goddard at erin.goddard@unsw.edu.au

Project Title: Understanding Climate Anxiety

Supervisor(s): Prof Michelle Moulds & Prof Ben Newell

Description: Anxiety about climate change and its consequences for the planet has been widely reported, particularly in young people, and the topic has received increasing attention in the psychological literature in recent years. However, the way in which psychologists conceptualise, measure and address climate anxiety in therapy all remain areas of discussion and ongoing debate. This project will involve conducting a critical review of the existing literature on climate anxiety with the goal of providing an up-to-date overview and recommendations for directions of future research.

Experience: None required. Experience with rodent handling and wetlab work preferred. 

Project Title: Exploration of infantile amnesia

Supervisor(s): Prof Rick Richardson

Description: Assist in behavioural training/testing of infant rats on a fear conditioning task. The project may involve examination of the impact of early-life adversity on memory, and/or the role of various neurotransmitters in the recovery of apparently forgotten infant memories.         

Experience: None required. Experience with R software desirable.

Project Title: Emotional regulation in adolescence

Supervisor(s): Prof Rick Richardson

Description: Assist in behavioural training/testing of adolescent rats on a fear conditioning task. The project may involve examination of the impact of chronic stress on fear extinction and/or the impact of social buffering on fear expression/extinction.     

Experience: None

Project Title: How are secondary fear memories encoded and consolidated in the brain? 

Supervisor(s): Dr Nathan Holmes & Dr Jessica Leake

Description: Studies investigating the biological basis of fear memories typically use protocols involving a single dangerous event. In reality, traumatic experiences, such as abuse, are often repeated and this has implications for how fear memories are processed in the brain. Our laboratory has found that forming an initial fear memory depends on a cascade of biochemical processes in a specific region of the brain, the amygdala. This includes: 1) the activation of NMDA receptors, whose biophysical properties make them ideally suited to detecting coincidences between environmental stimuli and danger; and 2) synthesis of new proteins, which is thought to be critical for stabilization (or consolidation) of new fear memories so that they can be activated by appropriate retrieval cues. However, we have also shown that the same mechanisms are not required for forming a second, related fear memory. The goal of this research is to determine how secondary fear memories are encoded and stored in the brain. This goal will be achieved using a combination of behavioural and pharmacological manipulations in laboratory rats. 

Experience: None

Project Title: The role of expectations in visual attention

Supervisor(s): Dr Kelly Garner 

Description: We will be examining how learning about rewards, and building expectations, influences where and when people decide to pay attention, and assessing the impacts this has on perception. The role involves using eye-tracking methods to collect behavioural data, as well as recruiting participants and conducting some data analysis. This role is particularly well-suited for someone who would like to gain experience in eye-tracking methods and in asking questions about how we attend to the world around us.

Experience: Some experience with data analysis and coding is an advantage, but not necessary for the role.

Project Title: On how the brain combines previous experience to influence visual attention   

Supervisor(s): Dr Kelly Garner 

Description: You will join an existing project that is looking at how brain function and structure relates to how we pay attention. The role will involve adapting existing pipelines in functional and structural brain data analysis to address questions about how the brain combines different sources of learned information when paying attention. The role is particularly well suited for someone with some experience in coding and multivariate data-analysis, who is looking to learn more about neuroscience and brain imaging.         

Experience: Some experience coding is required (Python, Matlab or R are of particular advantage), and experience in multivariate data analysis is a plus.

Project Title: The role of affect in placebo and nocebo effects

Supervisor(s): A/Prof Kate Faasse & Dr Kirsten Barnes 

Description: This study will look at how affect influences the formation of placebo and nocebo effects. The student will be involved in developing and pilot testing an affect induction to induce positive, negative, and neutral affective states. Then, the affect induction will be used in an online experimental paradigm that uses low frequency noise exposure to generate placebo and nocebo effects. We aim to test whether positive affect can enhance placebo effects and block nocebo effects, and whether negative affect has the opposite effect. The low frequency noise paradigm has already been developed and tested in a number of studies. All data collection will be online, using Qualtrics software and the Prolific recruitment platform, which will enable us to run both studies quite quickly, so that the student gets experience in study design, recruitment, and some data analysis (appropriate to their career stage and experience).

Experience: Familiarity with placebo and nocebo effects is useful but not essential.

Project Title: Exploring the experience and management of side effects from antidepressants

Supervisor(s): A/Prof Kate Faasse & Dr Matthew Coleshill  

Description: This survey study will explore the experience of side effects from antidepressants, support received from health professionals in managing the experience of side effects, as well as the acceptability of educational interventions to reduce the experience of nocebo-related side effects through a survey of people diagnosed with depression who have been prescribed antidepressants. The student will be involved in data cleaning and data analysis appropriate to their career stage and experience following completion of data collection in late 2022. The aim of the study is to better understand the type of support people taking antidepressants receive from health professionals to manage side effects (e.g. behavioural modification, dose titration, etc), as well as to examine the acceptability of primarily preclinical educational interventions to reduce nocebo-related side effects in a target clinical population.

Experience: Familiarity with, or an interest in, the nocebo effect, depression and its clinical management, and quantitative data analysis is useful but not essential.

Project Title: Modelling food insecurity in the rat

Supervisor(s): Dr Zhi Yi Ong

Description: The prevalence of food insecurity has steadily increased since 2014, with about 30% of the population worldwide currently food insecure. Food insecurity is associated with learning deficits and mental health issues, but the underlying mechanisms are unclear. Animal models are useful to dissect the neural mechanisms of food insecurity on subsequent behavioural changes. Thus, this project will involve generating a preclinical rat model of food insecurity to examine how food insecurity affects how, when and what one chooses to eat. The student will gain experience in developing rodent models and assessing feeding behaviours through a variety of behavioural tasks

Experience: Experience with rat handling is desirable though not necessary.

Project Title: Restoring gut-brain signal sensitivity to overcome overeating

Supervisor(s): Dr Zhi Yi Ong & Dr Kenny Ip

Description: Overeating is a major contributor to the increasing rates of obesity worldwide. Individuals with reduced gut-brain signal sensitivity are more likely to overeat and gain weight. Here, we will examine whether restoring gut-brain signal sensitivity can prevent overeating. This project will involve genetic manipulation strategies to restore gut-brain signal sensitivity, home-cage food intake monitoring and behavioural tasks to measure feeding behaviours.

Experience: Experience with rat handling is desirable though not necessary

Project Title: Psychological mechanisms underlying the mental health of adult refugees: a systematic review and meta-analysis

Supervisor(s): Prof Angela Nickerson

Description: This project would involve working in the Refugee Trauma and Recovery Program in the School of Psychology at UNSW. We are currently conducting a systematic review and meta-analysis to (1) identify which psychological mechanisms may be implicated in the onset and maintenance of mental health difficulties in refugees following trauma and (2) evaluate the quality of mechanism research in the refugee literature using a novel theoretical framework. This Vacation Research Scholarship would involve providing research support by (1) screening scientific research to determine their eligibility for inclusion in the review, (2) conducting manual searches of the literature (e.g., by backward citation searching), and (3) tabulating and synthesising research findings. This project would suit a student with an interest in refugee and human rights issues, who is interested in learning high-impact research methodologies that are intended to contribute to changes clinical practice, policy, and research practice. This research would lead to increased knowledge regarding the experiences of refugees, what mechanisms may be targeted to enhance their mental health and wellbeing, and hands on experience with systematic review and meta-analysis methodologies.

Experience: None

Project Title: Individual differences in sensitivity to anger provocation

Supervisor(s): Dr Elizabeth Summerell & Prof Tom Denson

Description: Aggression is most common in the presence of provocation. However, little is known about the specific situations or events that may provoke anger and/or lead to subsequent aggression. This project aims to develop a comprehensive taxonomy of anger provocations and provide a specific framework to organise and categorise these triggers. We will also examine individual difference factors that cause some individuals to be more sensitive to certain kinds of provocations.  

Experience: None

Project Title: Evidence-based initiatives for equity, diversity, and inclusion in STEM 

Supervisor(s): A/Prof Lisa Williams, Dr Sarah Ratcliffe & Dr Jessica Bergman 

Description: To achieve equity, diversity, and inclusion (EDI) in science, technology, engineering and mathematics (STEM) in Australia, systemic changes are required. Funded by the Australian Government, this project is reviewing, informing, developing, and implementing evidence-informed, impact-focused initiatives for effective achievement of EDI in STEM. The research project involves examining trends in awarded research grants, assessing the effects of anonymised grant applications, and reviewing and evaluating initiatives supporting EDI in the STEM workforce. During the Summer Vacation Research Program selected students will develop skills in literature and data analysis, synthesis, and appraisal, and experience in applying research for structural-level change. The research conducted will contribute to evidence-based recommendations, tools, and initiatives supporting governments, organisations, and sectors to effectively achieve equity in STEM. The project is suited to students seeking to be a part of science supporting systemic changes for equity. 

Experience: None

School of Materials Science and Engineering Projects

Project Title: Cathodes for High Energy Density and High Voltage Sodium Ion Batteries

Supervisor(s): A/Prof Pramod Koshy & Dr Sajjad Mofarah

Description: The project involves fabrication of high energy density and high voltage sodium ion battery (SIB) cathodes using room temeprature electrochemistry. In this project, the following topics will be studied:Thermodynamic analysis, electrochemical synthesis, and various characterization tests such as XRD, Raman, FTIR, SEM, TEM, EPR, and BET surface area analysis.

Experience: None

Project Title: MOF-Derived Metal Based Catalysts for Water Splitting Applications

Supervisor(s): A/Prof Pramod Koshy & Dr Sajjad Mofarah

Description:This project focuses on development of novel materials as oxygen evolution reaction catalysts for water splitting. This project is based on fabrication of metal organic framework (MOF) as precursor, and subsequent thermal conversion of MOF into metal derivatives and carbon. In addition to synthesis process this project encompasses a comprehensive range of characterization tests, including XRD, Raman spectroscopy, SEM, TEM, XPS, and BET surface area analysis.

Experience: None

Project Title: Ce-based Metal Oxides and Heterojunctions for Energy Storage Applications

Supervisor(s): A/Prof Pramod Koshy & Dr Sajjad Mofarah

Description: This project aims to develop a novel and highly unstable cerium-based coordination polymer as a precursor for the synthesis of MO nanospheres with a solid sphere architecture for the purpose of energy storage pseudocapacitance application. The project entails several characterisation techniques, including XRD, Raman spectroscopy, FTIR, SEM, TEM, EPR, and BET surface area analysis.

Experience: None

Project Title: Semiconductors for renewable energy applications

Supervisor(s): A/Prof Judy Hart

Description: In this project, computational methods will be used to investigate and develop semiconducting materials for renewable energy applications, such as catalysts for clean fuel generation. The project can be adapted based on the interests of the student.

Experience: None

Climate Change Research Centre Projects

Project Title: Effects of Lower Stratospheric Stability on the Southern Annular Mode

Supervisor(s): Dr Martin Jucker

Description: The Southern Annular Mode (SAM) is the main mode of variability in the Southern Hemisphere. It manifests itself via a poleward shift of the band of strong westerly winds called the jet stream, and has known impacts on rainfall and surface temperatures throughout the Southern Hemisphere. This project will investigate whether the temperature structure in the lower stratosphere just above the tropopause has an influence on the SAM, and if so, tries to quantify its influence. This is based on recent findings in relation to ozone anomalies and sudden stratospheric warmings, which both have been shown to have an impact on surface weather. The project will use existing climate data, and use an idealised climate model to run custom numerical simulations.

Experience: None

Project Title: Analysis of hail in Australia’s tropics

Supervisor(s): Dr Tim Raupach

Description: Australia’s most hail-prone regions are on the east coast from north of Brisbane to south of Sydney. However, the largest hailstone ever recorded in Australia fell in the sub-tropics, just north of Mackay, and the possibility of hail occurrence extends well into the tropics. In particular, a region around Burketown in Queensland shows as a hotspot of hail probability in radar, satellite, and hail-proxy records. In this project, we will investigate hail occurrence in convection-resolving simulations of the atmosphere around Burketown. The student will gain experience in analysing the output from high-resolution weather models, in atmospheric science, and in scientific programming. The project will increase our understanding of the atmospheric conditions leading to hail formation in the (sub-)tropics, a region in which hail occurrence is not well understood.

Experience: To complete this project experience with python is essential and experience with analysing large datasets is a plus.

Project Title: The future of renewable energy droughts in Australia

Supervisor(s): Dr Doug Richardson & Dr Anna Ukkola

Description: Transitioning from fossil fuels to renewable energy is a key part of Australia’s pledge to reduce greenhouse gas emissions. An energy system with more renewables, however, is susceptible to variations in the weather and climate. Extended periods of cloudy, wind-less weather can mean solar and wind production isn’t enough to meet demand. This can be compounded when hydropower reservoir levels are low. The extent to which solar, wind and hydropower droughts will co-occur in the coming decades is unknown, but is crucial in enabling the energy sector to transition its systems to rely more on renewables. In this project, the student will use climate model data to quantify how likely it is that Australia will experience compound wind, solar and hydropower droughts under different emissions scenarios for the coming century. The results will be used to inform future research into the impacts of climate change on Australia’s energy system.

Experience: Some programming experience (ideally Python or R) is desirable.

Project Title: Building a Human-Labelled Database of Atmospheric Rivers and Tropical Cyclones for AI Training

Supervisor(s): Dr Sanaa Hobeichi

Description: Leveraging artificial intelligence (AI) to detect weather features, such as atmospheric rivers, fronts, and tropical cyclones, holds great promise in advancing our understanding and prediction of extreme precipitation events. However, to train Artificial Intelligence models effectively, we need a comprehensive database of weather features. In this project, the student will contribute to the development of a comprehensive human-labelled database of atmospheric rivers or/and tropical cyclones and fronts using high-resolution climate model output.

The student will undergo training on how to identify atmospheric rivers by visualizing the high-resolution climate model output. Following this, they will employ suitable data labeling software to draw polygons over the identified atmospheric rivers, generating a meticulously labeled dataset.
By creating this database, the student will be contributing to the development of the training samples needed to train AI models to autonomously detect and classify weather patterns.

Experience: None

Project Title: Quantifying subgrid clouds in high-resolution simulations

Supervisor(s): Dr Abhnil Prasad Prof Steven Sherwood

Description: The characteristics of numerically simulated clouds and convection depend on the resolution of weather and climate models. Subgrid clouds are parameterized in coarse-resolution models but are often resolved at higher resolutions. Such clouds are essential in understanding shallow convection and can significantly affect the radiation budget if unaccounted for in our current models. This project aims to quantify the characteristics of subgrid clouds by comparing several associated cloud and radiation fields simulated at different resolutions from a numerical weather prediction model to ground-based and available satellite observations. The main objective of the project is to understand how well sub-cloud variability is captured to varying resolutions in model simulations.

Experience: The project requires Python programming skills in analysing data.

Project Title: Role of different astronomical configurations on past climate

Supervisor(s): Dr Himadri Saini & A/Prof Laurie Menviel

Description: A key understanding of the mechanisms behind past climate changes helps us prepare for the occurrence of similar processes in the future. Using Earth System Climate Models (ESMs), we are now able to simulate the past climate of thousands and millions of years ago. One of the fundamental requirements to simulate past climate is Earth’s orbital parameters, which include obliquity, eccentricity, and precession. Changes in obliquity, axial tilt of the Earth’s axis, have been known to impact the total solar radiation on Northern and Southern Hemisphere during summer, which, in turn, affects the air temperature, sea surface temperature and sea ice over the North and South pole respectively. The student involved in this project will analyse available data of a simulated climate under different astronomical configurations, with a particular focus on the sea ice extent in the Southern Ocean.

Experience: No prior knowledge of past climate changes is crucial here, but students with background in atmospheric/oceanic sciences are preferred. The candidate is required to be familiar with the use of Python, or other data visualization tools.

Project Title: Understanding the biogeochemical consequences of marine extreme events

Supervisor(s): Dr Neil Malan

Description: Marine extreme events have a significant impact on marine ecosystems and are predicted to intensify as the ocean warms. However, our understanding of the impacts and nature of marine extremes is mostly limited to studying temperature at the surface, due to a lack of observations. Insights into the response of the ocean to marine extremes can only be gained by examining and contrasting the specific sites which have sufficient long-term observations.

The student will participate in taking a global inventory of long-term observational sites, identifying marine extremes, and exploring the differences between the ocean’s response to extremes in different locations. This project will contribute to our understanding of global subsurface ocean extremes and their impacts on marine ecosystems.

Experience: None

School of Chemistry Projects

Project Title: Light-activated DNA nanotechnology

Supervisor(s): Dr Felix Rizzuto

Description: We use DNA as a building block for nanotechnologies in healthcare and materials science. This project will develop protocols to reversibly assemble polymers built exclusively from DNA, using light. You’ll learn microscopy techniques like TEM, biomolecular characterisation methods, and polymer analysis skills.

Experience: None.

Project Title: Quantifying solvent effects in ionic liquids - how to get the reaction outcomes you want!

Supervisor(s): A/Prof Jason Harper

Description: Being able to get a reaction to happen in the way that you want (rate, selectivity) is really important in chemistry. But new solvents (like ionic liquids - which are organic salts that are liquid) are frequently insufficiently understood so reaction outcomes are not predictable. This project will examine some key benchmark reactions in ionic liquids and their mixtures to quantify reaction outcomes - so that prediction of reaction outcome and solvent choice become a reality.

Experience: Chemistry major with at least 12UoC chemistry, preferred 36 UoC.

Project Title: Computational Chemistry for Sustainable Technologies

Supervisor(s): Dr Martina Lessio

Description: Project description: Our group uses computational tools to investigate a variety of phenomena, molecules, and interfaces that are relevant to sustainability applications. In particular, we are interested in catalysis, water remediation, and  material conservation. Example of active projects available in the group are:

1) Developing new ligands for toxic contaminants removal from water for solid substrates such as metal-organic frameworks;

2) Study existing and new transition metal catalysts for converting CO2 and plastics into useful products;

3) Study of relevant material/solution interfaces for artwork and heritage conservation. The summer project will focus on one of these aspects, depending on student interests and current research developments in the group.

Experience: None

Project Title: Anode-Free Batteries: Advancing Performance and Safety in Energy Storage

Supervisor(s): Dr DJ Kim

Description: The objective of this project is to design, develop, and optimise an anode-free battery, a promising next-generation energy storage solution with potential for significant improvements in performance and safety compared to conventional lithium-ion batteries. Anode-free batteries eliminate the need for graphite anodes, offering higher energy density, faster charging, and reduced risk of dendrite formation, ultimately leading to safer and more efficient energy storage devices.

Experience: None

Project Title: Bridging the Gap: Integrating Molecular-Level Motion for Enhanced Machines

Supervisor(s): Dr DJ Kim

Description: The remarkable precision in controlling molecular-level motion observed in vital natural processes suggests a promising avenue for substantial progress by bridging the gap between biological systems and the current generation of synthetic molecular machines. These machines consist of meticulously arranged functional groups that, akin to the macroscopic machines we encounter daily, collaborate harmoniously to perform tasks that surpass the capabilities of their individual components. The central goal of this project is to investigate the integration of distinctive structures to influence the chemistry and function of molecular machines.

Experience: Any organic chemistry lab coursework.

Project Title: Improving online assessment practices: Comparing online and paper-based examinations

Supervisor(s): Dr Sara Kyne

Description: This project is analysing both paper-based and online examinations in first year STEM courses across Australia. The aim of the project is to determine best practice for summative examinations, including design that considers both technological as well as pedagogical aspects required to deliver effective and authentic assessments.

Experience: Some experience with statistical methods and/or coding (for example Python or R) would be considered desirable 

School of Mathematics & Statistics Projects

Project Title: Automated data analyses using natural language processing

Supervisor(s): Prof Scott Sisson

Description: Captain Kirk arrives in a new star system at the bridge of his space ship and says “Computer, scan for anomalies!”. The computer attempts to understand what Kirk means, explores what data streams are available, decides what assumptions it can make, decides which models/analyses fit these criteria and implements them, performs diagnostics and eliminates those approaches that don’t work, summarises the results, and then replies to Kirk “There is an anomalous gravitational reading on the second moon of the third planet.” How can we design and build such an autonomous data analyst? This project will explore, high level, how such a system might work.

Experience: A good understanding of statistics, data science, mathematics and data analysis techniques. A strong interest in coding and in creating tools for automating analyses.

Project Title: Tools to support reproducible research

Supervisor(s): Prof Scott Sisson

Description: Arxiv.org is an open, public research service for hosting research preprints and makes them available to anyone. It is a hugely valuable service in making research open to the world. However, with so much research being done in recent years, there is concern that some of the research outcomes in published papers, don’t contain enough information to reproduce the research. Ideally all research would be perfectly reproducible. It would be a great service if papers could automatically be awarded a “Reproducibility Index Score” that would be larger the more reproducible the work is, that anyone could look up at any time for any research published in the world. This project will explore how such a Reproducibility Index might work as both an index, and a public research service.

Experience: A good understanding of and interest in scientific research. A strong understanding of coding, and willingness to learn how systems such as arxiv.org work.

Project Title: Statistical Methods for Optimization

Supervisor(s): Dr Zdravko Botev

Description: In this project you will explore data science methods for solving linear and quadratic programming optimization. You will implement these methods on a computer and compare them with current best optimization algorithms like ADMM, interior-point, etc.

Experience: Programming and Advanced Calculus

Project Title: Understanding the causes of disease through genetics

Supervisor(s): Dr Daniel S Han & Jonathan L. Ciofani (BMedSci MPH MD)

Description: Mendelian randomization is a method of examining the causal effect of modifiable exposures on disease outcome through genetic variation in the population. First proposed in 1991 by Gray and Wheatley the method has been reliably used to detect the causal influence of alcohol consumption (modifiable exposure) on blood pressure (disease outcome). Moreover, the properties of genetic variants make them insusceptible to reverse causation and confounding which plague traditional epidemiological studies. In most mendelian randomization studies, the relationship between an exposure and disease outcome is assumed to be linear. However, we know that this is not true for many exposures. For example, low and high extremes of BMI may be associated with increased mortality highlighting an inherently non-linear relationship. Furthermore, present mendelian randomization studies and, more problematically, the broader medical community fail to account for differences in population groups in detecting exposures that lead to disease. This project aims to explore different methods to perform mendelian randomization studies when there is a non-linear relationship between the exposure and outcome and when there are significant genetic differences between population groups.

Experience: Some programming experience (in MATLAB, Python, R, C++ or equivalent) will be essential.

Project Title: Random walks faster than exponentials

Supervisor(s): Dr Daniel S Han

Description: When exploring an abstract high dimensional space, a random walk needs to sample positions for some time before an equilibrium distribution is found. In most random walks, the exponential waiting time gives the fastest convergence to an equilibrium distribution. This project will focus on using a mixture of exponential and Mittag-Leffler waiting times to explore if faster convergence to an equilibrium distribution can be achieved.

Experience: Some programming experience (in MATLAB, Python, C++ or equivalent) will be essential.

Project Title: Recreating the morphology of neurons from detailed brain maps

Supervisor(s): Dr Daniel S Han

Description: In recent years, detailed synapse-scale maps of animal brains have become available. For examples see the fly brain (https://v2.virtualflybrain.org/org.geppetto.frontend/geppetto) and parts of the mouse brain (https://www.microns-explorer.org/cortical-mm3). Now it has become possible to explore the morphology of neurons in the brain down to each individual synapse. By leveraging these datasets and finding conserved statistical quantities across all neurons in the brain, this project will attempt to find general mathematical algorithms that enables the recreation of neuron morphology.

Experience: Some programming experience (in MATLAB, Python, C++ or equivalent) will be essential.

Project Title: Exploring Second Order Optimization Methods for Best Subset Selection in Data Science

Supervisor(s): Dr Sarat Moka & Dr Zdravko Botev

Description: The task of selecting the best subset of features from a dataset is a crucial and challenging problem in data science. While recent advancements have concentrated on employing first-order continuous optimization methods for best subset selection in linear and non-linear regression models, this project aims to investigate the potential of second-order optimization techniques, such as Newton's method and its variants, for addressing this challenge.

By delving into second-order optimization methods, we seek to gain a deeper understanding of their numerical and analytical advantages and the challenges they may present in the context of best subset selection. Through this exploration, we hope to enhance our ability to identify the most relevant and significant features in datasets, ultimately leading to more accurate and interpretable regression models.

Experience: Linear Algebra

Project Title: Exploring the theory of Navier-Stokes equations and their applications to fluid flow

Supervisor(s): A/Prof Chris Tisdell

Description: Navier-Stokes equations are of immense theoretical and physical interest. These partial differential equations have been used to better understand the weather, ocean currents, water flow in a pipe and air flow around a wing. However, the theory of the equations has not yet been fully formed. For example, it has not yet been proven whether solutions always exist in three dimensions and, if they do exist, whether they are smooth - i.e. they are infinitely differentiable all points in the domain. The Clay Mathematics Institute has identified this as one of the seven most important open problems in mathematics and has offered a US$1 million prize for a solution or a counter example. In this project we will examine existence and smoothness of solutions to problems derived from the Navier-Stokes equations that arise in laminar fluid flow in porous tubes and channels. Channel flows - liquid flows confined within a closed conduit with no free surfaces - are everywhere. In plants and animals, they serve as the basic ingredient of vascular systems, distributing energy to where it is needed and allowing distal parts of the organism to communicate. In engineering, one of the major functions of channels is to transport liquids or gases from sites of production to the consumer or industry. Such a project will involve the nonlinear analysis of boundary value problems and some numerical approximations.

Experience: Some experience and interest in differential equations

School of Biological, Earth & Environmental Sciences

Project Title: Understanding the effects of extreme heat on desert mammals

Supervisor(s): A/Prof Katherine Moseby

Description: Heatwaves are becoming more frequent and more intense under climate change but their effects on threatened mammal species are largely unknown. In this project, a student will collect field data on the movement, survival and habitat use of threatened mammals over the summer months at an arid zone field site. We will use accelerometers, GPS transmitters, remote cameras and direct observation to assess the changes in behaviour due to extreme heat. The mammal species may include the numbat, bandicoot or feral cat. The student will have some input into project design.

Experience: Field skills are desirable but not essential. The student must be prepared to travel to a remote field site in South Australia and stay for 6 weeks in on site accommodation.

Project Title: Activated carbon for methane reduction from ruminants

Supervisor(s): Prof Torsten Thomas & Dr Tim Charlton

Description: Methane produced by the microbes of ruminants represents between 7-18 % of total anthropogenic greenhouse gas emissions. Activated carbon has been shown to decrease methanogenic microbes and hence decrease methane emission. The research project will focus on the interaction of activated carbon particles and microorganism and analyse microbial development over time. Insight into the interaction of microbiomes with activate carbon will provide new scientific knowledge on how methane emission from ruminants can be further reduced.

Experience: Some background in microbiology and/or experience in lab work would be appreciated.

Project Title: Fossilied insects from the Southern Highlands

Supervisor(s): Matthew McCurry

Description: There are very few fossil sites in Australia that preserve Cenozoc insects, which has made it difficult to interpret how historic changes in climate impacted insect communities. In this scholarship a student will identify already collected insects from a fossil site in the Souther highlands of NSW and compare the proportion of insect orders to other insect communties, living and extinct. The results will provide foundational data on Australia's fossil history and valuable data for future studies on the interation between abiotic changes and insecet community composition.

Experience: None

Project Title: Habitat use of threatened and non-threatened stream-breeding frog species

Supervisor(s): Dr Jodi Rowley

Description: This project will investigate the habitat use of threatened and non-threatened stream-breeding frog species in eastern Australia using a combination of fieldwork and the FrogID (frogid.net.au) dataset.

Experience: Useful to have experience in the field and/or in analysing datasets.

Project Title: Insect sensory systems, sexual selection, and body shape

Supervisor(s): Prof Russell Bonduriansky

Description: This project will investigate the scaling of sensory structures in an insect species with extreme sexual dimorphism. Using morphometric analysis on field-collected samples, statistical approaches will be used to quantify body shape variation and test key hypotheses about the evolution of sexually selected traits.

Experience: None

Project Title: Can chatbots be our friends?

Supervisor(s): Prof Rob Brooks

Description: Test the ways in which a variety of chatbots use techniques known to build friendship in human-human interactions.

Experience: None

Project Title: Understanding the timeline of recovery for corals and coral symbioses following ongoing environmental disturbance

Supervisor(s): A/Prof Tracy Ainsworth & Charlotte Page

Description: Coral bleaching and mortality can severely alter the benthic community on coral reefs. Here you will join a team of researchers studying the impacts of environmental disturbances, including the breakdown of coral symbioses (bleaching) and loss of corals, from coral reef ecosystems (mortality). In this scholarship you will learn how to identify different corals and algae in a subtropical system, how to use automation tools to assist in identification of different members of the reef, and how to identify the health of corals within a complex coral reef community.

Experience: None

Project Title: Episymbioses and invertebrate partnerships of temperate corals.

Supervisor(s): A/Prof Tracy Ainsworth & Sophie Vuleta  

Description: Corals have a range of symbioses and partnerships which extend beyond the well-known photoendosymbiosis between corals and dinoflagellates. Corals also have partnerships with invertebrates that use the colonies as a safe home and source of nutrients, in return these invertebrate episymbionts remove waste from the host and can also aid in nutrient provision. Here you will work with researchers identifying the eipsymbionts of temperate corals from several locations along the New South Wales coastal habitats in which they are found.

Experience: Understanding of invertebrates and interest in learning about invertebrate identification.

Project Title: Assessing gender and career stage in coral health review publications

Supervisor(s): A/Prof Tracy Ainsworth & Samantha Burke

Description: Coral and coral reefs science is a rapidly growing area of research globally. Understanding where research is undertaken provides a unique insight into the role of different communities, cultural backgrounds, and career stage in contributing to this global effort. Here you will work with researchers investigating coral reef scientific effort to investigate the gender and career-stages of coral reefs researchers.

Experience: Data management experience would be an advantage. Should be conformable with engaging with researchers via email and other communication networks.