Python Job: Data Science Research Scholarships 2022

THE OPPORTUNITY
The summer scholarship program offers currently enrolled undergraduate students the opportunity to carry out research projects during summer 2022/2023. The program will run for 8-10 weeks and we have 7 opportunities available. The scholarship will be up to a value of $5000, dependent on duration in the program ($500 per week).

These projects provide hands-on research experience across a range of topics:

Project 1: Investigating DNA methylation landscape of oesophageal cancer using cutting-edge nanopore long-read sequencing
Oesophageal cancer is a poor prognosis cancer and is often diagnosed at late stages. High mutation burden and genome rearrangements are common in this cancer type. The overall aim of this project is to investigate the relationship between the methylation landscape and genomic instability. Nanopore sequencing is an exciting technology enabling simultaneous whole genome sequencing and methylation profiling. This project is suitable for a motivated student familiar with genome data and interested in investigating nanopore methylation profiles in unstable genomic regions of oesophageal cancer.

Project 2: Genetic sequence variants in lupus RNA-sequencing
Systemic lupus erythematosus (SLE) is a severe and chronic autoimmune disease. Patients with SLE are heterogeneous with differences in symptoms and responses to treatments. We previously studied the expression levels of all genes in immune cells from patients with SLE to better understand the underlying molecular mechanisms of disease; this project will extend the analysis to investigate genetic sequence variants contained in RNA sequences from patients.

Project 3: Investigating the impact of somatic mutations at single-cell resolution
Somatic, or acquired, mutations are a pervasive and underappreciated source of genetic variation, and a primary cause of cancer and other diseases. In the new era of single-cell genomics, a key technical challenge is assigning somatic variants to individual cells, in order to better understand their functional consequences in disease. The aim of this project is to pilot methods for detecting somatic mutations in single cells, using a unique combination of genomic and single-cell transcriptomic data, including long-read nanopore sequencing data. This project would suit a motivated individual familiar with genomic data, and an interest in understanding the cellular impact of disease-associated somatic variants.

Project 4: Detecting mutational signatures in clonally-expanded blood cells
Mutational signatures are characteristic patterns of genetic mutations caused by exposure to mutagens, or ineffective DNA repair. Using large genomic datasets of blood-derived DNA, this project will investigate the origins of mutations in individuals with and without disease. This project would suit a motivated individual familiar with genomic data, and an interest in understanding the origins of disease-associated genetic mutations.

Project 5: Calculation of polygenic risk scores across multiple genomic sequencing platforms
Polygenic risk scores are an emerging tool for summarising the influence of many genetic variants on an individual's risk of almost any common disease. Although traditionally generated from genotyping array data, many other cutting-edge genomic platforms have the ability to generate polygenic risk scores, along with other relevant genetic information. This project will take advantage of orthogonal genomic datasets generated on a group of 10 individuals, and use this information to compare and contrast their relative performance in the calculation of polygenic risk scores and detection of other classes of genetic variation. This project would suit a motivated individual familiar with genomic data, and also offers an opportunity to engage with an industry partner.

Project 6: Computational approaches to accelerate nanopore DNA analysis
Nanopore sequencing is a cutting-edge technology for DNA analysis. A nanopore device outputs fine electrical signals that can be translated – or ‘base-called – into DNA sequences, which we use to diagnose patients with genetic disease. Unfortunately, the software used to perform this base-calling process (named ‘Dorado’) is painfully slow and computationally expensive. Our goal is to re-engineer Dorado, applying software engineering principles to accelerate nanopore base-calling. If successful, this will have great benefit to the genomics/biotechnology community.

We are looking for a student who is keen to learn advanced engineering concepts, such as NN inferencing and software profiling. This is not just another boring deep learning project, but will instead require deep thinking and careful problem solving. A good understanding of C/C++ is essential. Experience in torch is a bonus.

Project 7: Visualising tandem repeat expansions in genetic disease
Repetitive DNA sequences (eg: CAG-CAG-CAG) in the human genome are common. While these play important roles in gene function, there are certain repeats that become expanded in length and cause genetic disease. A well-known example is the ‘CAG’ repeat expansion that causes Huntungton's Disease. Healthy humans have between 10 and 35 repeats of this motif. Affected patients will have 36 or more repeats. Visualising these repeats in modern DNA sequencing datasets is critical for disease diagnosis.

We are looking for a creative student to build a new software package for fast and flexible visualisation of tandem repeat sequences in human genome samples. The tool will automate the process of inspecting >50 clinically informative repeat sequences across many patient DNA samples, and annotating their likely disease consequences. Scripting level language (e.g. python or R) is essential. Some biology/bioinformatics/genomics knowledge would be useful, but is not essential.

ABOUT GARVAN
The Garvan Institute of Medical Research is an independent Medical Research Institute (MRI) in Sydney, delivering scientific and clinical impact on a global basis and in partnership with organisations that share our vision. We are proud to be one of Australia’s largest and most highly regarded MRI’s.

Our vision is global leadership in discoveries to impact and our enduring purpose is to impact human health, by harnessing information encoded in our genome.

We seek to see our world-class discovery research achieve life-changing impacts, not only for individual patients with rare diseases, but for the many thousands affected by complex, common disease.

Garvan promotes a diverse workplace and is committed to the principles of equity, diversity, inclusion and belonging.

HOW TO APPLY
All applications must be submitted via the Garvan Careers site [Workday].
Applications from other sites/channels will not be considered.

Part One:
Your application via the Garvan Careers Site/Workday should include:

• Copy of your CV/resume [no more than five (5) pages]

• Cover letter outlining which project(s) you are applying for [one page only]

• Copy of your academic transcript/s

[Note - Our system requires these documents to be compiled into one PDF document]

Part Two:
In addition to submitting your application via Workday, please complete the Student Applicant Form at: tinyurl.com/garvansummer

CLOSING DATE
The position will remain open until filled. We will be reviewing applications as they are received, and so we encourage you to submit your application as soon as possible.

We aim to have positions filled by the end of October 2022 for project commencement in early December 2022. All applicants will be notified of the outcome of their application by the end of October 2022.

Job Type: Full-time

Salary: $500.00 per week