This is an exciting opportunity for two motivated and talented PhD students to join the UKRI Research Hub in AI for Collective Intelligence (ai4ci.ac.uk). The Hub is a UKRI National AI Research Hub involving universities from each of the UK’s four constituent nations and over forty stakeholder partners from across academia, government, charities and industry. It is an applied, interdisciplinary effort to develop novel AI for collective intelligence, addressing key societal challenges. Based at the University of Bristol, these studentships will play an important role in developing the Pandemic Resilience research theme led by Leon Danon.

An essential part of analysis of emerging infectious disease threats is to make sense of a large stream of data from many disparate sources and make robust estimates of key disease parameters such as the reproduction number. During the COVID-19 pandemic, data was rapidly collected, collated, analysed and modelled to support central government decisions and inform the public. This work was done largely through a huge collective effort by experts, scientists and public health officials, yet AI played a modest role. Now, as AI tools mature, there is a need to develop novel AI, tailored to infectious disease to speed up the generation of key evidence.

The successful candidates will have an interest in interdisciplinary work at the interface between infectious disease epidemiology and AI and will join a large network of collaborators through JUNIPER (maths.org/juniper), the United Kingdom Health Security Agency (UKHSA) and policy links. They will develop cutting-edge technology to enable robust and reproducible analyses, tested on a large body of historical infectious disease data including (but not limited to) COVID-19.

The ultimate aim is to develop new expertise and be ready to contribute to response efforts in the face of new emerging infectious disease threats like Avian Influenza and mPox.

Candidate requirements:
Applicants must hold/achieve a minimum of a merit at master’s degree level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate degree. Please note, acceptance will also depend on evidence of readiness to pursue a research degree.

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