Research / Senior Research Officer – Single Cell and Computational Genomics

Job No: GC201974
Location: Darlinghurst, NSW

The Garvan Institute of Medical Research is one of Australia’s leading medical research institutes, with over 600 scientists, students and support staff.  We pioneer study into the most widespread diseases affecting our community today, including cancer, neurodegenerative and mental diseases, disorders of the immune system, diabetes and obesity, osteoporosis and other skeletal disorders. 

The research program of the Single Cell and Computational Genomics lab 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.

Postdoctoral positions are available in three major research projects.

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? This is of considerable interest because, with a few exceptions, human tissue and organ systems cells are continually renewed from stem cell populations, and thus demonstrating temporal-specific genetic contribution to disease risk will enable better targeted therapies to be developed. 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. The long-term objects of this program are the translation of research into clinical settings through developing new diagnostic tests, partnering for clinical trials, or developing treatment guidelines in collaboration with clinical partners.    

The Opportunity 

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. The long-term objects of this program are the translation of research into clinical settings through developing new diagnostic tests, partnering for clinical trials, or developing treatment guidelines in collaboration with clinical partners.    

The role will have the following responsibilities:

  • Preforming experiments and analysis of data generated either by the single cell and computational genomics laboratory, collaborators, or publicly available
  • Recording and assisting with design and interpretation of experimental procedures and results
  • Conducting leading-edge informatic analysis of genetic and genomic datasets.
  • Meeting with Associate Professor Joseph Powell and members of the laboratory.
  • Attending, discussing and reviewing current and future techniques within Garvan’s Bioinformatics (BUG) meetings.
  • Making presentations of research progress to the entire Cancer + Genetics and Epigenetics Research Divisions and other collaborative groups as required.
  • All staff are required to comply with Garvan’s Work Health & Safety (WHS) Policy and work in accordance with the WHS management system at all times.
  • Other duties as assigned.

The role will be offered for full time for 2 years with potential for extension.

About You 

We are looking for someone with 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, multi-tasking; 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. Candidates are expected to establish independent research projects, and to generate high impact publications, providing outstanding opportunity for further career development in academia.

The successful candidate will possess the following key skills and attributes:

  • The incumbent should possess a PhD in Computational Biology, Statistical Genetics, Bioinformatics, Genomics. or equivalent experience in a related field
  • Excellent computational background, especially in the management of large data sets in HPC environment
  • High proficiency in programming and scripting languages (e.g. C/C++, Java, Perl, Python)
  • Advanced user of the R programming language and R-based statistical packages and tools, such as those available from the Bioconductor project for high throughput genomic data analysis
  • Good knowledge of statistics and presentation of molecular/clinical data
  • Demonstrated experience using version control for code development and curation
  • Experience in the analysis and interpretation of large genomic data sets (WGS, RNA-Seq, scRNA-Seq)
  • A proven track record in leading peer-reviewed publications
  • Familiarity with the ethical issues and guidelines relating to the use of human tissue and clinical data for research
  • Excellent problem-solving skills
  • Good communication skills and strong in team work and collaborative research
  • Excellent project management and organisation skills
  • Ability to work independently and meet deadlines

 How to Apply

All applications must be submitted via the Garvan Careers site via the link below. Applications from other sites/channels will unfortunately not be considered.

https://garvan.applynow.net.au/jobs/GC201974

 Your application should include: 

  • A cover letter
  • Your resume including at least 2 referees
  • Copies of relevant qualifications / academic transcripts

Only applicants with working rights in Australia are eligible to apply for this role. Incomplete applications will not be considered.

Closing Date: This role will remain open until filled. As we will be reviewing applications as they are received, we encourage you to submit yours as soon as possible.

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