Tag Archives: PhD studentship

MRC-funded PhD studentships in Agent-Based Modelling

Here at the MRC/CSO Social and Public Health Sciences Unit at the University of Glasgow we recently announced a whole host of PhD topics for students looking to join us on our interdisciplinary quest to improve public health and reduce health inequalities.  The studentships are funded by either the Medical Research Council (MRC) or the University of Glasgow, and cover the full cost of tuition fees and provide a stipend.

Students who have a Masters-level degree already can jump right into the three-year funded PhD, or if you’re fresh out of undergraduate education you can join a four-year programme and get your Masters in the first year.

In the Complexity and Health Improvement Programme we are offering up a few potential topics on the application of agent-based models to public health challenges, supervised by myself, Rich Mitchell, Mark McCann, and Umberto Gostoli.  If you’re keen to get involved in this relatively new area of work in public health, do read through the topics and get in touch with the Programme Leader (and Unit Director) Laurence Moore as soon as you can, in order to discuss your proposal.

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Funded PhD opportunity at Teesside

Fully-funded PhD opportunity available! I’m looking for someone interested in working on agent-based modelling for healthcare applications. No fees and £20K stipend. These are four-year positions and you will be asked to contribute up to six hours per week of teaching (tutorials/demonstration only, no lectures), which is more work but also good for the CV. Click here and filter under ‘Computer Science’ to see my project.  For more about me, check out the various pages on this blog or my staff profile at Teesside.

Project description: This research will focus on the application of Agent-Based Modelling techniques to human social systems, with particular emphasis on digital health applications. In the context of public health, agent-based models can help us understand the complexities of health policy implementation and service delivery by modelling the multiple interacting processes underlying the health system. These models will investigate challenges in health and social care service delivery across a variety of spatial and temporal scales – from short-term studies of demands on accident and emergency services, to longer-term explorations of the pressures facing social care over the next several decades. Our multi-disciplinary team will work with members of the School of Health and Social Care here at Teesside, along with external collaborators and stakeholders. The project would be suitable for a graduate with a background in Computer Science, Artificial Intelligence, Statistics or Complexity Science with an interest in Public Health/Healthcare applications.

ACADEMIC FRIENDS: Please tweet/share this as widely as you can!

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