Junior to Senior Research Officers - Computational Genomics
The Computational Genomics Laboratory focuses on demonstrating the genomic mechanisms by which loci contribute to complex human diseases, and working towards early stage diagnosis methods and targeted therapeutics. To do so, we apply existing computational approaches, and develop our own statistical genetics methods for analysis of large-scale next generation sequencing data. Following in silico experiments, we perform functional validation of statistical observations using molecular techniques such as high-throughput genome editing and cell phenotyping. We have a very significant focus on the use of single cell sequence data and technology, due to the phenomenal resolution it offers in being able to identify differences in the genomics processes between individual cells. The laboratory drives projects in a number of areas of medical genomics research, but we also believe strongly in the value of collaboration between groups with differing expertise. We are committed to reproducible research practices, and open data policies.
Our three major research projects are:
Population genetics meets single cell sequencing
We have generated single cell RNA-sequence data from blood samples, along with SNP genotypes for a large cohort of healthy and unrelated individuals. This project will develop single cell eQTL mapping methods to firstly produce an atlas of cell-type specific and ubiquitous genetic effects on gene expression. Subsequently, by integrating population level GWAS and bulk RNA-sequence data, with medical records and vaccination history available to this cohort, work to identify the genetic and cell type specific mechanisms contributing to disease risk and immune response to pathogens.
Resolving the genetic mechanisms of complex human disease using stem cells
Using induced pluripotent stem cells, and differentiating them through intermediate to mature cell states allows us to study the genetic mechanisms that contribute to common diseases. This project will build on recent work from the Computational Genomics group to address two fundamental questions. Firstly, do the genetic (allelic) effects that contribute to disease vary as cells transit across their developmental lineage? Secondly, does genetic variation influence cell fate and cell developmental phenotypes?
Clinical translation of single cell sequencing for diagnosis and precision medicine
This project will focus on the further development of statistical methods for the prediction of cell states or types from clinical samples and their use in clinical decision making for precision treatment. The research will predominately focus on the development of new statistical and analytical methods, but with initial applications using single cell sequence data generated from liquid biopsies from lung diseases, cancers, and immune profiling.
We are seeking Junior to Senior Research Officers to join Associate Professor Joseph Powell’s newly formed Computational Genomics Laboratory at Garvan.
The key responsibilities include:
- Preforming experiments and analysis of data generated either by the Computational Genomics Laboratory, collaborators, or publicly available
- Recording and assisting with design and interpretation of experimental procedures and results
- Develop work priorities and review research progress with Research Divisions such as Cancer and Genomics & Epigenetics
- Conducting leading-edge informatic analysis of genetic and genomic datasets
- Publish research outcomes under joint authorship in leading scientific journals
- Provide data for research proposal submissions to external funding bodies
- Discussing and reviewing current and future techniques within Garvan’s Bioinformatics (BUG) meetings
- Gain peer recognition by presentations at national scientific meetings in relevant field
- Provide general research guidance to more junior research staff
The position will be full-time for 3 years in the first instance.
A strong background in human genetics, cancer genetics and genomics, genetic epidemiology, and/or computational biology, bioinformatics preferred. Highly motivated individuals with a recent PhD and a strong track record of research as evidenced by publications; excellent written and verbal communication; expertise in bioinformatics DNA analysis software; strong attention to detail, good multi-tasking skills; and a willingness to learn new technologies are encouraged to apply. The applicant should have published in top tier journals and demonstrated an ability to successfully complete projects independently. The Research Officer is expected to establish independent research projects and to generate high impact publications, providing outstanding opportunity for further career development in academia.
How to Apply
All applications must be submitted via Garvan’s Careers site via the link below. Applications from other sites/channels will unfortunately not be considered.
Please include the following in your application:
- A cover letter
- Your resume including at least 2 referees
- Copies of relevant qualifications / academic transcripts
We are recruiting a number of positions and will be reviewing applications as they are received. Candidates are encouraged to submit their application as soon as possible.