Job no: 537732
Work type: Continuing (Contingent Funded)
Location: Canberra / ACT
Classification: Academic Level A
Salary package: $73,309 - $92,015 per annum plus 17% superannuation.
Terms: Full-time, Continuing (Contingent Funded)
- Join a diverse multidisciplinary team working across domains and scales to build a future science platform.
- Engage in collaborative research, based at the CSIRO, to solve significant science questions through analytical advances.
- Gain experience in the development of cutting-edge statistics, machine learning and artificial intelligence applied to real-world problems in biology, agriculture and aquaculture.
The Biological Data Science Institute (BDSI) is a academic unit in the College of Science that sits at the interface of data science and biological science. It aims to recruit, build and coordinate expertise in biological data science to accelerate the translation of biological data to biological knowledge. Operating in the space between traditional disciplines, the BDSI is positioned to collaborate across the ANU campus and with partner organisations to solve problems that have impact.
Multiple BDSI positions are being recruited in formal partnership with CSIRO to support their Future Science Platform in Machine Learning and Artificial Intelligence (MLAI FSP). This cohort will work with top scientists and engineers to develop, extend and leverage MLAI approaches to advance analytical frontiers in areas with direct applications to animal and plant breeding. The Postdoctoral Fellows will be embedded in a collaborative FSP research team at the CSIRO Black Mountain site adjacent to the ANU Acton campus, while also being members of the ANU Biological Data Science Institute.
These positions are being recruited into the “Bioprediction” activity within the MLAI FSP. The Postdoctoral Fellows will be part of a multidisciplinary team working to develop and apply generalised statistical and analytical methods for automating the analysis of biological data to address problems of data integration, uncertainty, bias, dependent variables and samples, and heterogeneous data types. This may include the formal evaluation of methodology to demonstrate its functionality, performance, robustness and fitness for purpose in the application context.
There is funding to support this position for three years.
For further information, please contact Professor Eric Stone E: email@example.com
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In order to apply for his role, please make sure that you upload the following documents:
- statement addressing the selection criteria, and
- A current curriculum vitae (CV).
Applications which do not address the selection criteria may not be considered for the position.
Please note: The successful applicant must have rights to live and work in this country.
Applications close: 08 Nov 2020 11:55:00 PM AUS Eastern Daylight Time