*Research fellow position in causal machine learning for health policy*
Institution: Centre for Health Economics (CHE), University of York (UK) An important strand of Global Health Economics research at CHE is about policy impact evaluation using quasi-experimental research methods, with an increasing focus on the use of machine learning. We are seeking to appoint a Grade 6 Research Fellow to contribute to this research agenda, with a strong background in quantitative methods, such as econometrics, statistics and machine learning, and an interest in developing and applying those methods for the purpose of health policy impact evaluation. The Research Fellow will be part of a new, methodologically focussed research project, led by Dr Noemi Kreif. Role · To develop methods to design optimal health policy allocation rules, combining state-of-the-art approaches from causal inference and machine learning. · To extend causal inference and machine learning methods to fit the requirements of health policy evaluation, e.g. to consider health equity impacts when estimating optimal health policies. · The methods will be applied primarily in the context of two on-going policy evaluations: the National Health Insurance Programme in Indonesia, and the Family Health Programme in Brazil, using large survey and administrative data sets. Skills, Experience & Qualification needed Applicants are required to have the following qualifications: · BSc and/or MSc or equivalent in economics, health economics, statistics, mathematics or another related subject and a PhD or equivalent experience in a relevant quantitative field. · The post requires a knowledge of causal inference and machine learning methods, and experience in methodologically focussed research using statistical/econometrics methods. · Advanced skills in the use of R statistical software are essential, familiarity with Stata statistical software and Python programming language is desirable. · The ability to write up research work for publication in high profile journals, and good communication skills to engage with a wide-ranging audience is essential. · Experience in methodologically focussed research using statistical/econometrics methods is required. *This post is available fixed term for 24 months* *Interview date:* 6 October 2020 *For informal enquiries:* please contact noemi.kr...@york.ac.uk or marc.suhr...@york.ac.uk All details can be found on these links: https://www.jobs.ac.uk/job/CAX443/research-fellow https://www.york.ac.uk/che/news/news2020/research-fellow-job-vacancy/ -- James Cussens Room CSE/239 Dept of Computer Science University of York York YO10 5GE, UK Tel +44 (0)1904 325371 http://www.cs.york.ac.uk/~jc http://www.york.ac.uk/docs/disclaimer/email.htm
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