The Garvan Institute of Medical Research brings together world-leading clinicians and basic and translational researchers to break down barriers between traditional scientific disciplines and find solutions to disease. Founded in 1963, Garvan’s mission is to harness all the information encoded in our genome to better diagnose, treat, predict and prevent disease.
Our scientists work across four intersecting research themes: medical genomics, epigenetics, and cellular genomics; diseases of immunity and inflammation; cancer; and diseases of ageing affecting bone, brain and metabolism. In addition, three major Centres: The Kinghorn Centre for Clinical Genomics, the Garvan-Weizmann Centre for Cellular Genomics, and the Centre for Population Genomics.
The Centre for Population Genomics, a new multi-institution initiative is planned for a formal launch in August 2020. The Centre will focus on the development of cutting-edge tools and resources to facilitate the conversion of genomic data into improved diagnosis and treatment for Australians, the field known as genomic medicine. Ultimately, the Centre will generate and manage the largest sets of genomic and clinical data ever assembled in Australia, and apply these to solve a wide variety of scientific and medical problems. The Centre’s staff will operate from two physical sites: Garvan in Sydney, and the Murdoch Children’s Research Institute (MCRI) in Melbourne.
We are seeking a highly motivated genomic analysis expert to recruit and lead a team of computational scientists developing complex genomic analysis workflows on Australia’s largest human genomic data sets. The Genomic Analysis Lead will develop and implement a strategy for analysis of human data ultimately spanning more than ten thousand whole genome and single-cell transcriptome data sets from diverse Australian communities. This is a unique opportunity to play a leadership role in a new Centre that will shape the future of genomic medicine in Australia, and build resources with global impact.
Over the last ten years the human genomics community has collected an extraordinary volume of data on genetic variation in the human population, thanks to genome or exome sequencing performed on millions of people worldwide. However, much work remains to be done to ensure that these data can be translated into genomic medicine that benefits the entire population, in Australia and globally. This will require, for instance, platforms for storage and computing across millions of human genomes, new methods for analysis, and targeted strategies to ensure that all populations are represented in the next generation of reference databases.
The Centre for Population Genomics will build the tools and massive data sets required to integrate genomics into medicine in Australia. The Genomics Analysis Lead will be responsible for developing an analysis strategy for very large and diverse genomic data sets, for developing scalable pipelines for complex analysis, and for working closely with the Centre’s software development team to implement these at production scale. This individual will recruit and manage a team with diverse skills across computational biology, statistics, and human genetics to create these pipelines, perform analyses, and contribute extensively to the publication of high-impact science.
This position will report directly to the Centre Director, Daniel MacArthur, who previously led a team at the Broad Institute of MIT and Harvard in Boston that was responsible for the development and open release of the Genome Aggregation Database (gnomAD), a collection of genetic data from over 140,000 individuals that has become one of the most widely-used reference databases in human genetics.
The Genomic Analysis Lead can be located at either the Garvan in Sydney or the Murdoch Children’s Research Institute in Melbourne. To adapt to the impact of COVID-19, we will launch under a completely remote model – all staff will begin their employment working from home, and can begin their work without needing to relocate to Sydney or Melbourne.
This is a three-year full time role with high possibility to extend.
The key responsibilities include:
- Working with the Centre Director, other senior Centre staff, and external stakeholders to develop and implement strategic plans for analysis of the Centre’s large-scale genomic data sets, and to develop a broader scientific strategy for the Centre as a whole
- Building technically competent teams by recruiting and managing a team of computational staff scientists with diverse skills across the fields of computational biology, statistical and population genetics, and machine learning
- Developing and nurturing a culture of rigor and openness in software development and analysis, including following software development best practices, ensuring code developed by the Centre is made available as open-source software, and that Centre members approach the analysis of large data sets with extreme rigor and scepticism
- Leading meetings dedicated to code review and analysis best practices
- Meeting regularly with the Centre Director and other scientific staff and trainees to identify key priority areas for algorithm development, and externally developed software to be tested and applied to Centre data sets
- Liaising with the Centre’s Software Team to ensure that pipelines developed by the Genomic Analysis Team are rapidly and effectively productionised and deployed at scale on cloud-based platforms as well as on-premises hardware
- Developing plans for solving daunting technical challenges, such as QCing and analysing sequence data sets of enormous scale, by making full use of their team members and wider Centre resources
- Presenting internally and externally – including at national and international meetings – about the analysis work done at the Centre
- Contributing to (and in some cases leading) the generation of scientific publications and funding applications
The key skills and experience include:
- A PhD in computational biology, functional genomics, statistical genetics, population genetics, or a related field, and at least two years of postgraduate experience in the field; or an equivalent amount of direct work experience in these fields
- Highly autonomous and self-motivated: able to define and manage the execution of novel strategies for analysis across a wide range of technical areas, from basic sequence data set quality control through to population genetic analyses, without tight specifications in advance
- Good written communication skills: able to contribute to, and in some cases lead, papers, grants, and technical reports
- Highly collaborative: more concerned with solving important biological problems by working with others than with securing individual credit
- A problem-solving mentality: able to navigate a complex and dynamic series of technical obstacles, and to pivot rapidly when needed, to build a first-of-its-kind research project; someone who identifies problems even if they fall outside their immediate mandate, and works with other team members to solve them