We invite applications for a Post-Doctoral Research Associate to join the New Approaches to Bayesian Data Science: Tackling Challenges from the Health Sciences programme. This £3M programme is funded by EPSRC, and brings together research groups from the Universities of Lancaster, Bristol, Cambridge, Oxford and Warwick. Research Associate positions are available in each group to build a team that will work on developing new Bayesian and Computational Statistical methods, motivated and applied to challenges from Health. Active collaboration across the partner institutions, and with other project partners, is expected.
This goal of this exciting, cross-disciplinary research project is to develop new methods for Bayesian statistics that are fit-for-purpose to tackle contemporary Health Science challenges. Methodological challenges will be around making Bayesian methods scalable to big-data and robust to (unavoidable) model errors. In terms of application domain, the post holder will work within the area of statistical omics.
You should have, or be close to completing, a PhD in Statistics or a related discipline. You will work directly with the investigators to undertake and support the research necessary to achieve your university's aims within the grant. This will include, for example, publishing in leading statistical/application journals, presentation of research at workshops and conferences, developing code implementing new statistical methods, and active involvement in project meetings. You will be experienced in one or more of the following areas: Bayesian statistics, computational statistics, statistical machine learning, statistical genetics. You will have demonstrated the ability to develop new statistical methodology. We are particularly keen to encourage applicants with a strong computational skills, and are looking to put together a team of researchers with skills that cover theoretical, methodological and applied statistics. A demonstrable ability to produce academic writing of the highest publishable quality is essential.
Fixed-term: The funds for this post are available for 3 years in the first instance.
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The closing date for applications is 31 March 2020 with interviews taking place on 16th April 2020 (estimated date).
Please quote reference SL22665 on your application and in any correspondence about this vacancy. Informal enquiries are welcomed and should be directed to Professor Sylvia Richardson (Email: email@example.com)
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