Research Fellow in Modelling Collective Behaviour

University of Leeds School of Mathematics

Research Fellow in Modelling Collective Behaviour

Are you an ambitious researcher looking for your next challenge? Do you have an established background in the mathematics of decision-making and collective behaviour? Do you want to further your career in one of the UK’s leading research-intensive universities?

We are looking for a Research Fellow to join our project on Collective Behaviour of Cognitive Agents. This UKRI-funded project aims to develop new theories of individual and collective decision-making and motion in humans and animals.

You will work with Principal Investigator on the development of mathematical and computational models based on principles of rational decision-making, Bayesian inference and game theory, and integrate these with the latest biological knowledge and experimental results.

You will have a PhD in Applied Mathematics, Statistics, Physics, Engineering or a closely aligned discipline. You will also have the ability to conduct independent research and a developing track record of publications in international journals. In addition, you will have excellent communication, planning and team working skills.

To explore the post further or for any queries you may have, please contact:

, University Academic Fellow in Data Analytics

Tel: +44 (0)113 343 8988

Email:

Please note: If you are not a British or Irish citizen, from 1 January 2021 you will require permission to work in the UK. This will normally be in the form of a visa but, if you are an EEA/Swiss citizen and resident in the UK before 31 December 2020, this may be your passport or status under the EU Settlement Scheme.

Location: Leeds - Main Campus
Faculty/Service: Faculty of Engineering & Physical Sciences
School/Institute: School of Mathematics
Category: Research
Grade: Grade 7
Salary: £33,797 to £40,322 p.a.
Due to funding restrictions, an appointment will not be made above £33,797 p.a.
Working Time: 37.5 hours per week
Post Type: Full Time
Contract Type: Fixed Term (Fixed-term until 31 December 2023 (grant funding))
Release Date: Wednesday 24 March 2021
Closing Date: Wednesday 21 April 2021
Interview Date: To be confirmed
Reference: EPSMA1031

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