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Postdoctoral Research Associate

The University of Edinburgh - College of Science and Engineering, School of Biological Sciences, Institute of Ecology and Evolution

Location: Edinburgh
Salary: £37,099 to £44,263 Grade UE07
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 30th November 2023
Closes: 24th January 2024
Job Ref: 9095

Full time contract (35 hours per week) 

Fixed Term (36 months) 

A postdoctoral research position is available in the lab group of Dr Matthew Hartfield, funded by a ERC Consolidator Grant/UKRI Frontier Research Grant (SelectSelf – Rethinking Evolution in Self-Fertilising Species). I am looking for an enthusiastic and motivated postdoctoral researcher who is interested in evolutionary genetics and mating-system evolution.

The Opportunity:

The focus of the project will be to:

  1. Develop stochastic population-genetic models to determine the signatures of genetic adaptation in self-fertilising species, especially when proceeding via a multi-gene (polygenic) process.
  2. Translate these models into inference methods to determine the nature of adaptive evolution from genome sequence data, with applications to a large dataset of several self-fertilising Caenorhabditis species.

There will also be scope for the postdoc to (i) consider how these processes are pertinent in response to anthropogenic changes; (ii) develop their own research plans with an view to becoming an independent investigator.

The project will involve collaboration with partners within the UK and overseas. There are substantial funds within the grant for computing and conference attendance. The project will be funded for three years in the first instance, with a possibility for extension based on performance and financial availability.

Your skills and attributes for success:

  • Skills with theoretical and computational population genetics.
  • Experience with analysing genome sequence data.
  • PhD in a quantitative biological discipline (or another quantitative subject, e.g., computer science).
  • Knowledge of computational biology tools, including R and command-line interfaces.
  • Evidence of creativity and problem-solving to tackle scientific problems.
  • Ability to work independently.

To apply, please click on the ‘Apply’ button above

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