Undergraduate Scholarships

UNSW Science Vacation Research Scholarships (SVRS) 2021 - 2022 

Applications close Thursday 30 September 2021.

Are you a science student who would like the opportunity to experience the real world of scientific research first-hand?

Students in the penultimate (second last) year of their undergraduate program in Science or a related discipline are invited to apply for an SVRS to join a BABS research team and participate in research over the coming summer.

Each SVRS scholarship is valued at $3,800 and students will participate in a 6-week research project. 

The School facilitates collaborative research efforts across discipline boundaries for fundamental discoveries, generation of commercial opportunities and clinical research. BABS has key strengths in environmental microbiology, genetics and cellular biology, molecular medicine, and associated technology development in the areas of functional genomics and many facets of biotechnology. The School has a unique strength in combining fundamental biological and biomolecular sciences with strong applied biotechnology and medical focus. 

How to apply

The first step of the application process is to contact the supervisor of your chosen project to discuss the project's requirements. When you have decided on your project preferences please submit an application form by the closing date - 30/09/2021.

Full details (including how to apply) are provided on the Scholarships website and enquiries can be directed to science.adrt@unsw.edu.au.

SVRS Projects 2021 - 2022

Supervisor: Dr Matthew Baker

Email: matthew.baker@unsw.edu.au 

Description: 

In this project we explore the directed evolution of the flagellar motor in the lab by evolving it to swim under different energy sources and selecting for motility. Recent work in antibiotic resistance (eg by Michael Baym) has shown that the resistance of antibiotics occurs in lockstep when progressing through 10-fold increases in antibiotics. We aim to explore how motility evolves across interfaces, when a bacterium faces a change in environment between, for example, H+ and Na+ environments, and how the bacteria adapts to dwindling nutrient across this interface. This project has scope for designing and building custom tanks to optimise bacterial evolution using 3D printing and prototyping, as well as investigating microbiology and bacterial motility in multiple dimensions using layered swim devices. 

Supervisor: Dr Matthew Baker

Email: matthew.baker@unsw.edu.au 

Description: We utilise the high efficiency and self assembly of the flagellar motor to drive rotation of cells on patterned surfaces to control mixing and fluid flows in microfluidics. We have projects involving designing and building new devices to apply the flagellar motor onto other things. This would suit someone with an interest in DIY/maker culture. 

Supervisor: Dr Matthew Baker

Email: matthew.baker@unsw.edu.au 

Description: The evolutionary origins of the bacterial flagellum have been a subject of scientific and public controversy – how can evolution produce such a complex system? We believe we can make progress on the issue by updating old phylogenetic work with new datasets and improved models, and combining this with experimental evolution work being done in our labs. The project will be to assemble a well- organized database of flagellar proteins and explore sequenced bacterial genomes with genome browsers and similarity searches. The student will identify flagellar proteins and their evolutionary relatives, including recording their position in the genome. The student will also plan and conduct phylogenetic analyses, and then use synthetic biology to recreate these ancestors in a contemporary microbial ‘Jurassic Park’. 

Supervisor: A/Prof Cecile King

Email: c.king@unsw.edu.au 

Description: 

Ribonucleic acid (RNA) is ubiquitous - the most ancient macromolecule for life. The immune system evolved in the context of RNA and, since the role of the immune system is to protect us from infection, it evolved ways to distinguish foreign RNA derived from pathogens from our own “self” RNA. To do this, the immune system utilizes receptors that enable specific recognition of RNA. Accumulating evidence shows the association between multiple human diseases and RNA sensing genes in the immune system, highlighting the important role of RNA sensing in the function of the immune system.

In this project, we will analyse RNA sensing molecules inside cells and the RNA that they bind, both when cells are in the steady state and when they are exposed to foreign RNA. You will learn methods including immunoprecipitation of RNA binding proteins and methods that enable detection of the RNA that binds to these receptors. This project is designed to further our understanding of the immune stimulating features of RNA and how the pathways involved in RNA sensing are regulated.

Supervisor: Dr Emily Oates

Email: e.oates@unsw.edu.au 

Description: 

Our research is focused on the discovery of new human disease genes, establishing the biological pathways that are impacted by disease-causing variants (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 new disease gene (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.

Experience: 

Prior knowledge/experience required for this project: All applicants should have strong interest in human genetics – and a curious mind. Science or medical science students with a background in genetics (2nd and 3rd year level) or medical students with a background in fundamental and/or clinical genetics would be very suitable. Bioinformatics/programming skills useful but not essential.

Supervisor: Dr Emily Oates

Email: e.oates@unsw.edu.au 

Description: 

This project involves the use of state-of-the art short and/or long read RNA sequencing technologies to (1) Advance our understanding of normal skeletal and cardiac muscle isoform biology, and (2) Characterise the transcript-level impacts of mutations responsible for paediatric muscle diseases. Data generated by this project will also be used to inform the development of muscle disease-focused genetic drug therapies aimed at modifying the expression of transcripts impacted by genetic muscle diseases to improve clinical outcomes.

Experience: 

Prior knowledge/experience required for this project: All applicants should have strong interest in human genetics – and a curious mind. Science or medical science students with a background in genetics (2nd or 3rd year level) or medical students with a background in fundamental and/or clinical genetics would be very suitable. Bioinformatics/programming skills very useful but not essential.

Supervisor: Dr Emily Oates

Email: e.oates@unsw.edu.au 

Description: 

This project involves the use of state-of-the-art genomic and RNA sequencing technologies, as well as detailed clinical phenotyping and natural history analyses, to advance our understanding of “Titinopathies”. These are an important emerging group of cardiac and skeletal muscles disorders caused by disease-causing variants (mutations) in one of the largest genes in nature – TTN (titin). In collaboration with an international army of clinicians and researchers, we have established a large cohort of titinopathy patients, 30 of which were described in a recent high impact publication (Oates et. all, Congenital titinopathy: comprehensive characterisation and pathogenic insights. Ann. Neurol. 2018). The goal of this project is to broaden our understanding of the clinical, muscle pathology and imaging features, and the biological basis of this important group of disorders.

Experience: 

Prior knowledge/experience required for this project: All applicants should have strong interest in human genetics – and a curious mind. Science or medical science students with a background in genetics (2nd or 3rd year level) or medical students with a background in fundamental and/or clinical genetics would be very suitable. Bioinformatics/programming skills very useful but not essential.

Supervisor: Dr Fatemeh Vafaee

Email: f.vafaee@unsw.edu.au 

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. (Example of Papers: (Zandavi and Vafaee, NeurIPS 2021, Zandavi et al, IEEE Cybernetics 2021).

Experience: 

Students need to have experience in programming and interest in machine learning/artificial intelligence methods applied to biomedical applications.

Supervisor: Dr Fatemeh Vafaee

Email: f.vafaee@unsw.edu.au 

Description: 

Repositioning existing drugs for new indications is an innovative drug discovery strategy offering the possibility of reduced cost, time and risk as several phases of de-novo drug discovery can be bypassed for repositioning candidates. Biopharmaceutical companies have recognised advantages of repositioning, and investment in the area is dramatically increasing. With the rapid advancement of high-throughput technologies and the explosion of various biological and medical data, computational drug repositioning has become an increasingly powerful approach to systematically identify potential repositioning candidates. My lab is running multiple research projects advancing the field of computational drug repositioning. We are developing computational tools and databases which integrate massive amounts of biological, pharmacological, and biomedical information related to compounds into advanced machine learning or network-based models to predict accurate repositioning candidates. Example of papers: (Azad et al, Briefings in Bioinformatics, 2020), (Azad et al, Patterns, 2021, http://dx.doi.org/10.1016/j.patter.2021.100325).

Experience: 

Students need to have experience in programming and interest in data science.

NOTE: If you identify a BABS staff member whose work you are interested in but they do not have a project listed on our website, you are encouraged to approach them to inquire whether they would be interested in offering a SVRS project.