The role of Research Associate sits in the UNSW Data Science Hub located within the School of Mathematics & Statistics. The UNSW Data Science Hub is a major strategic initiative of UNSW Science. It aims to cultivate and promote foundational and applied research in Data Science with a focus on environmental, physical and health sciences.
About the role
- $96K – $105K plus 17% Superannuation and annual leave loading
- Fixed-Term (2 years)
- Full-time (35 hours per week)
The role works closely with Prof. Robert Kohn and his colleagues at UNSW and Dr Amir Dezfouli and leading scientists and engineers at Data61. See https://scholar.google.com.au/citations?hl=en&user=94Dz5GYAAAAJ&view_op=list_works&sortby=pubdate for Robert’s publications, and https://scholar.google.com/citations?user=o5ym1RsAAAAJ for Amir’s.
Specific responsibilities for this role include:
- Contribute independently or as a team member in collaborative research with a focus to enhance the quality of research outcomes in the discipline area.
- Conduct research in the application of complex statistical and machine learning techniques to models of decision making.
- Undertake specific research project/s under the guidance of a research leader and contribute to the development of research activities.
- Coordinate research activities and participate in the setting of future research directions of the project.
- Assist with the supervision of research students in the research area where required.
- Act as a conduit to efficiently draw together the expertise of researchers from both UNSW Sydney and Data61/CSIRO to best tackle the research challenges.
To be successful in this role you will have:
- PhD or equivalent qualification in mathematics, statistics, physics or an alternative field with a strong mathematical and statistical background.
- Strong knowledge and demonstrated ability in at least one of Bayesian statistics, Reinforcement learning, computational statistics and machine learning methodology, including variational inference, Markov chain Monte Carlo methods, Gaussian processes, mixture modelling.
- Familiarity with deep learning and different neural network architectures.
- Superior ability to program in a high-level language, such as Python and R, with an application of version control.
- A strong research track record (relative to opportunity) as evidenced by publications in leading journals or conferences.
- A capacity to initiate and conduct independent research.
- A capacity to attract and effectively supervise research students.
For more information and to apply, please follow this link.
Applications close: January 31st, 2022