Postdoctoral/Research Fellow557012Canberra / ACT, ACT, Australia, 2601Fixed TermClosing at: Jan 19 2025 at 23:55 AEDTClassification: Academic Level A/BSalary package: $85,010 - $131,227 per annum plus 17% superannuationTerm: 3x Full-time, Fixed Term (Up to December 2027)The PositionThree Academic Positions Are Available For The Project "Analytics For The Australian Grains Industry" (AAGI) Within The ANU Biological Data Science Institute (BDSI).
The Successful Candidates Will Carry Out The Project On Three (3) Major Research Topics:Statistical design and modellingBioinformatics and molecular phenotypingMachine learning and image analyticsThese positions will be part of a collaborative partnership between ANU and the Strategic Partners (Curtin University, University of Queensland, and University of Adelaide) of the Analytics for the Australian Grains Industry (AAGI).The PersonWe are looking for three (3) academics with a PhD (or who will be awarded a PhD within six months of the appointment commencement) and experience in statistics, data science, machine learning, bioinformatics, quantitative biology, or closely related fields.
Candidates must possess strong scientific programming skills, demonstrated experience working with real data, and a substantial commitment to reproducible and transparent workflows.
They should also have evidence of experience relevant to the fields of data science, data analytics, statistics, machine learning, bioinformatics, or quantitative biology.For the Research Fellow (Academic Level B) position, candidates should provide evidence of their ability to articulate and pursue innovative research in the fields of data science, data analytics, statistics, machine learning, bioinformatics, or quantitative biology.
They should also present a vision for the activities they will undertake at ANU.Desirable RequirementsExperience in mixed models, experimental design, image analytics, machine learning, transcriptomics, or molecular phenotyping.Experience in the biological or agricultural sciences.Learn more about the ground-breaking research and work class facilities of Biological Data Science Institute here.For more information about the position please contactDr Emi Tanaka on E: at ANUThis is an opportunity to work with a world class University that undertakes cutting edge research and has a strong tradition in research-led teaching excellence.We OfferFlexible working arrangements including hybrid arrangements working both on our beautiful, green campus and working remotely.Generous paid parental leave entitlements of up to 32 weeks.
We are one of the leading employers in Australia for parental leave entitlements.Designated parent rooms, quiet spaces and childcare facilities on campus.Career support, training, mentoring & upskilling opportunities.For more information on a range of lifestyle, financial and non-financial rewards and programs, please click here.A Diverse and Inclusive TeamANU is introducing measures to support the recruitment, inclusion and retention of employees with disability.
To find out more, please click here.
ANU is a large, diverse employer with staff working across numerous professions.
We welcome applications from people of all backgrounds and identities and from individuals who may have had a non-linear career path, career gaps or career breaks.To ApplyTo be considered for this position, please upload the following documents:A current curriculum vitae (CV).No more than a two-page summary addressing your suitability against the selection criteria.The committee will consider candidates that do not meet one or more aspects of the selection criteria.If you require adjustments to participate in any of the above assessments, please contact our HR team at E: .
Any adjustment request or the disclosure of disability will not be communicated to the selection committee without the candidate's consent and it will not have any bearing on hiring decisions.The successful candidate will be required to undergo a background check during the recruitment process.
An offer of employment is conditional on satisfactory results.
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