A 12-month (8.75 hours/week) research position is available on the UK Medical Research Council-funded
Project Tailoring health policies to improve outcomes using machine learning, causal inference and operations research methods<https://gtr.ukri.org/projects?ref=MR%2FT04487X%2F1> . This project is led by the Centre for Health Economics at the University of York in collaboration with the University of Bristol and the Harvard School of Public Health (USA). The overarching research question of the project is: which subgroups of individuals or communities should be 'treated' to maximise the health policy maker's objective function, subject to constraints? The project involves two case studies: Social health insurance expansion in Indonesia and the Family Health Programme (FHP) in Brazil. The research position covers the 2nd year of the project. In the 1st year we have been working on combining machine learning and causal inference methods for evaluating heterogeneous impacts of health policies. The goal of the 2nd year is to extend this work to estimate optimal health policies under relevant objective functions and constraints. The project would suit an individual with interests and skills in machine learning, causal inference, constrained optimisation and real-world applications of AI methods. Details are available here: https://www.bristol.ac.uk/jobs/find/details/?jobId=260624 For informal enquiries contact james.cuss...@bristol.ac.uk It may be possible to conduct this research "remotely" (without moving to Bristol). On the other hand Bristol is a great city! James Cussens Dept of Computer Science, University of Bristol https://jcussens.github.io/ Funded PhDs available in Bristol in the following areas: Data Science<http://www.bristol.ac.uk/cdt/compass/>, Interactive AI<http://www.bristol.ac.uk/cdt/interactive-ai/>, Cyber Security<http://www.bristol.ac.uk/cdt/cyber-security/> or Digital Health<http://www.bristol.ac.uk/cdt/digital-health/>.
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