Bioinformatics & Cellular Genomics
The Facility
St Vincent’s Institute (SVI) www.svi.edu.au is an internationally recognised independent research organization, based on the St Vincent’s Hospital Campus on the edge of Melbourne’s CBD. The Institute has a dedicated team of over 150 talented research staff and students, who are committed to improving the health and life-expectancy of Australians. We focus on common diseases that represent major health issues for Australians today, including diabetes, bone diseases, cancer, cardiovascular disease, obesity and Alzheimer’s disease.
The Laboratory
The Bioinformatics & Cellular Genomics Laboratory is a newly funded group at SVI, established to solve the challenges of analysing and interpreting the large-scale biological data generated from medical research activity. In a jointly funded arrangement between SVI and the Melbourne Integrative Genomics Group (part of Melbourne University School of Mathematics and Statistics) and under the direction of NHMRC Fellow and Oxford graduate Dr Davis McCarthy, the Bioinformatics & Cellular Genomics Laboratory is capable of using large-scale studies of DNA and single-cell genetics to drive future medical discoveries.
BRIEF SUMMARY
The Position
We are seeking a motivated and successful postdoctoral Researcher to manage an independent project in single-cell genetics, developing new computational methods and open-source software to enable cloud-scale analyses of single-cell data. You will implement statistical and machine learning approaches and coordinate the processing and analysis of ‘omic data, identifying opportunities to customise more efficient workflows and methods where warranted.
The position also plays an important role in the overall performance and scientific activities of the laboratory as you will contribute to publications, assist in the supervision of students and present at seminars and lab meetings. The researcher will also have an organisation-wide responsibility in collaborating closely with the researchers of the wet-lab laboratories, providing computational expertise on experimental design and data analysis.
The successful incumbent will have a PhD (or equivalent) in a computational discipline relevant to bioinformatics and cellular genomics (bioinformatics, statistics, machine learning, computer science, applied mathematics, physics or similar) and possess advanced skills in using computer programming and scripting in R or Python and, ideally, familiarity with one or more of C++, Go, Nim, Rust, Java, Perl or SQL programming languages. You will have a demonstrated ability in the use of Unix-based systems, computing clusters and related queueing systems and in large-scale data analysis and management. Ideally you will have prior experience working in high-performance computing environments, including academic and/or commercial cloud computing platforms and experience using bioinformatics workflow management software (e.g. Snakemake, Nextflow, CWL). Your track record in bioinformatics, genomics, computational biology or other relevant quantitative fields will be evidenced by high-quality publications. Demonstrated experience developing open-source software and reproducible data analyses will be highly regarded.
Salary commensurate with qualifications and experience, ranging from AUD 83,000 – $90,000 per annum, plus:
9.5% superannuation
generous $15,900 FBT exempt salary packaging
Applications addressed to Dr Davis McCarthy should include the following:
Current CV
Covering letter addressing selection criteria, as outlined on the Position Description
Enquiries Dr Davis McCarthy dmccarthy@svi.edu.au
Application Email Address : hr313@svi.edu.au
MAIN JOB PURPOSE
The goal of SVI’s Bioinformatics and Cellular Genomics lab is to solve the challenges of analysing and interpreting large-scale biological data. We are broadly interested in the use of computational approaches to drive biological discovery and develop methods and software for the analysis of data produced by modern sequencing technologies, particularly single-cell genomic data. Further, we are interested in studying the effects of changes in DNA on gene expression in individual cells and in developing the necessary computational toolkits to enable large-scale studies of single-cell genetics.
The roles of a Research Officer are: 1) to conduct research on a defined project(s) within the overall interests of the laboratory; 2) to assist with the supervision of students; 3) to contribute to the overall maintenance of the laboratory, to 4) to participate in associated scientific activities, including institutional seminars, committees, etc.
KEY RESPONSIBILITIES
1. Manage an independent project and conduct computational analyses and methods development.
Develop computational methods, approaches, and software to enable single-cell genetics.
Adapt and/or develop original computational and analytical methods in support of existing and future research.
Implement statistical and machine learning approaches for genomics data analysis in open-source software.
Coordinate the processing and analysis of ‘omic data.
Implement and develop efficient pipelines for the pre-processing and analysis of a wide range of multi-omics data and where necessary develop new custom bioinformatics methods and/or pipelines.
Organise data, research, and analysis procedures.
Collaborate with wet-lab biologists, provide expertise on experimental design and manage the collaboration
Analyse the results of experiments conducted by collaborators and keep records of experimental and analytical results.
Maintain knowledge of relevant scientific literature, techniques/technologies and issues
Undertake research in a transparent and documented manner, in accordance with the Australian Code for Responsible Conduct in Research and SV’s Research and Governance guidelines
Performance measures
Data analyses are designed carefully and performed competently, efficiently and accurately
Methods and software development is carried out competently, efficiently and accurately, adhering to the Lab’s ethos of open and reproducible science
Projects are completed with the responsible management of resources and consumables
Knowledge is kept up to date through regular reading of literature to support all aspects of the research and to contribute to defining new directions
2. Contribute to laboratory publications:
Provide analysis of data from specific collaborative projects
Assemble data and results into figures for manuscripts and grant applications
Write manuscripts for publication in consultation with the Lab Head
Performance measures
Data analyses are completed with minimal delay
Preparation/contribution to publications, grant applications, etc
3. Contribute to laboratory administration/maintenance:
Maintain detailed (electronic) laboratory notebooks (or equivalent), digital data servers, documentation of code repositories, descriptions of computational analyses and other records
Provide technical expertise in the development and management of scientific computing environments to support the work of the laboratory (e.g. some light sys admin work).
Contribute to the maintenance of the laboratory’s repositories of data and of computer code.
Develop procedures to support reproducible research in the lab and Institute.
Performance measures
Laboratory notebooks (electronic notebooks or equivalent) and digital records are up to date
Datasets and code repositories are well-documented and well-maintained
Data analyses are well-documented and fully reproducible
4. Present at laboratory and unit meetings:
Attend and participate at regular laboratory and unit meetings
Prepare data and analyses, and present at these meetings
Performance measures
Active participation and professional contribution at all meetings
5. Supervision and teamwork
Contribute to the mentoring/supervision of undergraduate and/or graduate students
Provide training to laboratory assistants and students in specific methods/approaches/techniques
Make a positive contribution to the effectiveness of, and positive working relationships within, the laboratory group.
Provide collaborative support to others in the group and assist in the smooth running of projects.
Provide training and assistance with bioinformatics analyses to other members of the laboratory, as well as external collaborators as appropriate.
Collaborate with other SVI and University of Melbourne groups to provide bioinformatics support and identify experimental design/data analysis issues that would benefit from bioinformatics expertise.
Work with external collaborators.
Performance measures
Strong, harmonious and effective working relationships are developed and maintained with other members of the laboratory and collaborators within SVI and at other institutions
Knowledge and expertise is shared with team members and collaborators
6. Participate in activities within the institute and broader scientific community:
Attend regular the weekly institute seminars and make a contribution to the discussion
Engage with the SVI Postdoctoral Association
Engage with the Australian Bioinformatics and Computational Biology Society and/or Statistical Society of Australia and/or EMBL Australia
Attend and present (when the project is at an acceptably mature stage) at the national scientific meetings of the above societies as well as other local symposia/meetings and, where possible, international meetings
Performance measures
*Active participation with the SVI Postdoctoral Association and relevant scientific societies
Presentation of seminars
7. Occupational health and safety
SVI has a duty of care to all employees to provide a safe work environment. All employees must also take responsibility for their own safety, and that of fellow workmates, and should apply a common-sense approach to work methods to minimize risk to themselves and others.
Performance measures
Adherence to SVI Occupational Health & Safety guidelines, including the wearing of personal protective equipment as provided
Use equipment in compliance with manufacturers’ or relevant guidelines
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