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Machine Learning of Epidemic Models

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  • Full or part time
    Dr D Wojtczak
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

The project is supported by the University of Liverpool Doctoral Network in Future Digital Health, which is directed at creating and maintaining a community of AI health care professionals that can realise the benefits that AI can bring to Health Care. The vision is that of a world-class centre providing high-quality doctoral training within the domain of AI for Future Digital Health. Each available PhD project has been carefully co-created in collaboration with a health provider and/or a healthcare commercial interest so that the outcomes of the PhD research will be of immediate benefit. The network will be providing doctoral training, culminating in a PhD, in a collaborative environment that features, amongst other things, peer-to-peer and cohort-to-cohort based learning. On completion students will be well-placed to take up rewarding careers within the domain of AI and Digital Health.
A PhD project on applying machine learning techniques to model and control of epidemics is available at the Department of Computer Science of the University of Liverpool, UK. The Department is the world-leading research centre with a particular strength in artificial intelligence and theoretical computer science.

In this project, we will look into two fundamental machine learning paradigms, reinforcement learning and Hidden Markov Models, and extend them to allow high-level logical constraints to be imposed on the model or the optimal control strategy that they learn. These techniques will then be implemented and applied in the context of learning and control of epidemic models. A good understudying of fundamentals of probability theory and at least intermediate algorithmic programming skills are necessary. Knowledge of probabilistic systems (Markov chains and Markov Decision Processes), reinforcement learning and Hidden Markov Models is highly desirable, and familiarity with automata theory and temporal logic is a plus.

We welcome talented and highly motivated candidates with good first degree (BSc or MSc) in
Computer Science, Mathematics or closely related subject. The applicant must have good English communication skills, both verbal and in writing. The successful candidate will be supervised by
Dr Dominik Wojtczak (Department of Computer Science,,
Professor Neil French (Institute of Infection and Global Health), and Dr Roberto Vivancos (Public
Health England).

Applications must contain a cover letter, a curriculum vitae or resume, copies of undergraduate and postgraduate transcripts, a 1-2 page research statement describing how the applicant’s qualifications and research interests would fit the project, and the names and contact information of academic references.

To apply for this opportunity, please visit:

Funding Notes

This project is funded by the University of Liverpool Doctoral Network in Future Digital Health, successful students will receive a studentship of tuition fees paid at the Home/EU rate for 3.5 years and a stipend of £15,009 per annum for 3.5 years. In addition, students will have access to a research support fund of £1,000 per annum for purchasing equipment, consumables and conference costs co-managed by the academic supervisor. Applications from international students are welcomed, however suitable arrangements will need to be made for the difference between the Home/EU and international rate.

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