Senior Research Associate in Pandemic Resilience
This is an open-ended with fixed funding position (with funding confirmed for 18 months) within the UKRI National AI Research Hub in AI for Collective Intelligence (AI4CI ). The Hub is a major national collaboration bringing together seven partner universities (Bath, Bristol, Cardiff, Exeter, Glasgow, UCL and Ulster) to pursue cutting-edge research at the intersection between the fields of applied AI and Collective Intelligence across five application domains (Pandemic Resilience, Smart cities, Financial Stability, Health Ecosystems and Environmental Intelligence) and two cross-cutting themes (Human-Centred Design and Infrastructure and Governance).
What will you be doing?
The primary focus of this post is to develop new AI approaches to Pandemic Resilience. The potential for AI to support our response to emerging epidemic and pandemic threats is underdeveloped and the post holder will be at the forefront of innovation in this emerging field. The successful candidate will have the opportunity to work with a range of policy-facing stakeholders, central and local government and pharmaceutical industry leaders. Specific responsibilities include:
* Contributing to relevant research case studies within the AI4CI Hub.
* Developing data pipelines, machine learning models, and smart agents in simulated and real environments to develop and test hypotheses around the application of AI in developing resilience to pandemics.
* Analysing historical real world observational data to identify where use of AI could play a role in resilience to pandemics
* Setting your own research objectives within the scope of AI4CI.
Collaborating with the rest of the AI4CI Research Hub on research and research-related activities, in particular outreach, training, networking, policy development and stakeholder-oriented activities as required.
You should apply if
* A PhD in statistics, machine learning, mathematical modelling or other relevant quantitative subject.
* Experience in infectious disease mathematical modelling.
* Experience with epidemiological data and analysis for policy.
* Experience with AI/machine learning/data science methods.
* Proven experience of collaborating with relevant non-academic stakeholder partners (e.g. WHO, MSF).
* Outstanding publication record, including evidence of publishing in top journals.
Additional information
To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:
Contract type: Open ended with fixed funding until 31/01/2027
Work pattern: Full time
Grade: J
School/Unit: School of Engineering Mathematics and Technology
This advert will close at 23:59 UK time on Tuesday, 10th June.
Interview dates will be confirmed in due course.
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