Research Associate (Post Doc)

open until filled
Natural Sciences, Life Sciences, Biology
University of York
York, United Kingdom
£33,309 per year GBP


The post holder will join the team of the National Science Foundation project “Dynamic ant networks: How environmental constraints and ecological context shape resource transport systems”. This international team is led by Matina Donaldson-Matasci, Harvey Mudd College, USA, Scott Powell, George Washington University, USA, and Elva Robinson, University of York, UK. The post holder will be based in the Department of Biology at the University of York under direct supervision of Elva Robinson, Senior Lecturer in Ecology.

The goal of the project is to develop a general theory for how environmental constraints and opportunities shape dynamic transport networks in biological systems. The project seeks to create a unifying modelling framework predicting how biological transport systems respond dynamically and adaptively to environmental pressures, balancing competing priorities such as cost, efficiency and robustness. This new model will be parameterised with existing data from Formica wood ants and newly collected data from Cephalotes turtle ants, and used to make broad testable predictions about the organisation of biological transport systems.


The successful candidate will extend the broad model that has been developed so far, apply it to specific cases, generate predictions and compare results with empirical data. The modelling will use a dynamic network approach. The candidate will work closely with a second research associate, who will focus on empirical data collection. The successful candidate will also have the opportunity to mentor undergraduates based at the University of York or Harvey Mudd College who are contributing to the project, and will be expected to contribute ideas for the empirical work in both laboratory and field. The candidate will also collaborate in the preparation of reports and articles and represent the research group at conferences.

Skills, Experience & Qualification needed

The successful candidate will have completed or be near completion of a PhD degree in an area of the biological, mathematical or computer sciences or related areas. The successful candidate will have experience of a range of quantitative research techniques and methodologies, including network analysis and modelling biological systems. Ideally, the candidate will have experience in studying ecology and behaviour, in particular social animal systems. The candidate will have the ability to work as part of a team and also to work independently using own initiative, and will have experience of presenting work at conferences and for publication.

Interview date: 7 October 2021

For informal enquiries: please contact Dr Elva Robinson on

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