Research Fellow in Modelling Collective Behaviour

University of Leeds

Leeds, United Kingdom

ID: 7061598 (Ref.No. EPSMA1003)
Posted: October 21, 2019

Job Description

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 Dr Richard Mann 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: 

Dr Richard MannUniversity Academic Fellow in Data Analytics on:

Tel: +44 (0)113 343 8988 or via email: R.P.Mann@leeds.ac.uk 

Additional Information 

The Faculty of Mathematics and Physical Sciences is proud to have been awarded the Athena SWAN Bronze Award from the Equality Challenge Unit, the national body that promotes equality in the higher education sector. Our equality and inclusion webpage provides more information.

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.
Working Time:  37.5 hours per week
Post Type:  Full Time
Contract Type:  Fixed Term (4 years due to grant funding)
Release Date:  Monday 21 October 2019
Closing Date:  Wednesday 20 November 2019
Interview Date:  To be confirmed
Reference:  EPSMA1003




 

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