Research Fellow in Modelling Evolutionary Processes (eco-evo-devo)

University of Southampton - Agents, Interactions & Complexity

We welcome applications for two postdoctoral researchers in the area of ‘evolutionary systems biology’ at the lab of Richard Watson at the University of Southampton. Two positions are available, each for a duration of two years, starting June 1st 2017.

The positions are part of a (£7.7M) umbrella project which aims to put to the test the predictions of the extended evolutionary synthesis (Laland et al. 2015, PRSB, 282:1813). The two positions available at Southampton will build on recent developments unifying evolutionary theory with learning theory (Watson & Szathmary, 2016, TREE, 31(2), 147-157). This work converts theoretical tools of learning systems, already well-developed in computer science, to deepen and expand our understanding of natural evolution. Both positions will use computational and/or mathematical modelling to explore the adaptive capabilities of different functional processes and different assumptions about the processes of and feedbacks within natural selection: the selective conditions in which it takes place, the variation on which it can act, and the heritability of that variation. We focus on modelling how these components of the Darwinian Machine (i.e. selection, variation and inheritance) change over time as a function of past evolution. Themes addressed within these projects include:

  • The evolution of developmental organisations, plasticity, and evolvability (evo-devo).
  • The evolution of ecological organisations, collective function and niche construction in ecosystems (evo-eco).
  • The evolution of reproductive organisations and transitions in individuality (evo-ego).

Co-investigators include John Odling-Smee (Oxford), Michael Wade (Indiana), Andrew Gardner (St Andrews), Charlie Cornwallis (Lund), Kevin Laland (St Andrews), Gunter Wagner (Yale) and Tobias Uller (Lund). As a part of this team, the candidates will also work closely with several PhDs dedicated to this project and on related projects. 

The successful candidates will build mathematical/simulation models to develop our understanding of how ecological, developmental and reproductive feedbacks alter evolutionary dynamics and test the utility of learning theory to characterise them. Appropriate skill sets include gene-expression dynamics/gene-regulation network modelling, ecological dynamics/community network modelling, theoretical population genetics, mathematical modelling of biological evolution, social evolution theory, comparative phylogenetics, theoretical quantitative genetics, adaptive dynamics, evolutionary game theory, computational individual-based modelling, complex adaptive systems, algorithmic/functional modelling of evolutionary adaptation.

Applicants must have a PhD in a relevant subject and be capable of building bridges that link between evolutionary biology and computer science. For example: i) A PhD in theoretical evolutionary biology (e.g. evolutionary systems biology, theoretical population genetics, mathematical biology, social evolution theory), with strong mathematical skills and experience in simulation modelling/programming, or: ii) A PhD in computer science/maths/physics (e.g. complex systems/dynamical systems modelling, machine learning, optimisation) with strong knowledge/experience of working on applications in theoretical evolutionary biology. 

Applications must include a CV, publications list, the names of three referees and a covering letter explaining your current interests and relevant background. 

Salary range £29,301-£36,001 depending on experience.

Further information:

 Application procedure:

You should submit your completed online application form at www.jobs.soton.ac.uk. The application deadline will be midnight on the closing date stated above. If you need any assistance, please call Suzanne Stone (Recruitment Team) on +44 (0) 23 8059 4043. Please quote reference 811616FP on all correspondence.

Further details:

We aim to be an equal opportunities employer and welcome applications from all sections of the community. Please note that applications from agencies will not be accepted unless indicated in the job advert.

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