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Research Fellow in Modelling Complex Systems

Are you an ambitious researcher looking for your next challenge? Do you have an established background in modelling complex systems? Do you want to further your career in one of the UKs leading research intensive Universities?

As part of the PIGSustain project funded by the Global Food Securityyou will work closely with a large team of researchers and stakeholders across multiple disciplines in leading institutions across the UK. You will use a systems modelling approach to investigate the resilience of a complex system, the UK pig industry, in response to projected future shocks and trends.

PIGSustain will gather data in order to understand how sustainable intensification and predicted climate changes are expected to impact on the entire pig industry – from the health, disease and welfare of the animals, to consumption patterns and retail prices, which ultimately impact farmers. Gathering information on emerging diseases with the UK pig population is particularly important for the team because, unlike any other animal, it is possible for pigs to translate animal diseases into human forms.

You will have a PhD (or close to completion) in modelling complex systems or a closely allied discipline along with experience in creating, writing, enhancing, and running code in R/Matlab/Python. Excellent communication skills with the ability to talk to different audiences is necessary, as you will be collaborating with a large team of researchers across multiple disciplines.

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

Lisa Collins, Professor of Animal Science

Tel: +44 (0)113 343 5940  email: L.Collins@leeds.ac.uk

 

Location:  Leeds - Main Campus
Faculty/Service:  Faculty of Biological Sciences
School/Institute:  School of Biology
Category:  Research
Grade:  Grade 7
Salary:  £32,004 to £38,183 p.a.
Working Time:  37.5 hours
Post Type:  Full Time
Contract Type:  Fixed Term (for 36 months)
Release Date:  Thursday 20 April 2017
Closing Date:  Thursday 18 May 2017
Interview Date:  Monday 12 June 2017
Reference:  FBSBY1066
Downloads:  Candidate Brief  

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