The lottery of life: How chance shapes the evolutionary dynamics of wild populations, NERC GW4, PhD in Biosciences studentship Ref: 3339

About the award

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP).  The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five Research Organisation partners:  British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology,  the Natural History Museum and Plymouth Marine Laboratory.  The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see

For eligible successful applicants, the studentships comprises:

  • An index-linked stipend for 3.5 years (currently £14,777 p.a. for 2018/19);
  • Payment of university tuition fees;
  • A research budget of £11,000 for an international conference, lab, field and research expenses;
  • A training budget of £4,000 for specialist training courses and expenses.

Up to 30 fully-funded studentships will be available across the partnership.

Students from EU countries who do not meet the residency requirements may still be eligible for a fees-only award but no stipend.  Applicants who are classed as International for tuition fee purposes are not eligible for funding.

Project details

Despite a large body of theory describing how genetic variation and selection shape evolutionary trajectories, theoretical predictions are often at odds with what we observe in the real world. Being able to understand the source(s) of this discrepancy would significantly advance our understanding of the evolutionary process and provide a much-needed understanding of the ability of population to persist in a world changing at unprecedented rates. Although considerable effort has gone into incorporating the complexities that are typical of wild populations into our models of evolutionary change, this crucially assumes that evolution is in essence predictable. However, there is a potentially important role for stochastic processes (i.e. chance) in shaping all steps of the evolutionary process. For example, non-relatives may be genetically more similar than relatives due to Mendelian sampling, two otherwise identical individuals may differ in reproductive success because one got lucky and the other not, and random genetic drift can be responsible for large genetic changes from one year to the next. However, as of yet we lack a comprehensive understanding of the importance of stochastic versus deterministic (but unknown) processes in shaping the evolutionary dynamics of populations.

Project Aims and Methods

To quantify the importance of stochasticity in shaping the evolutionary dynamics of wild populations, this project capitalises on over a decade worth of individual-based long-term data for a small and isolated population of snow voles (Chionomys nivalis) in the Swiss alps. Since 2006, all individuals have been caught, individually marked, weighed and measured. DNA samples allow for the assignment of offspring to their parents, resulting in a well-resolved multigenerational pedigree. Recently this population has provided a rare example of adaptive evolution-in-action, revealing an adaptive decline in body mass in response to a change in snow fall patterns. 
In this project, we will generate high-density whole-genome sequence data for individuals from different time periods, and of varying degrees of relatedness. By combining these with extensive morphological, life-history and pedigree data, as well as individual based simulations, we can quantify the relationship between pedigree and genomic relatedness, an individual’s long-term genetic contribution to the gene pool, and the role of selection versus drift in shaping allele frequency changes. Together, this will provide a unique insight into the genomics of adaptation in a wild vertebrate and the evolutionary process in general.
This project capitalises on a uniquely rich and powerful dataset that allows for answering a wide range questions, and the student is encouraged to shape the project according to their interests.


The student will receive training in, among others, the statistical analysis of large datasets, individual-based simulation and the analysis of NGS data. This will be provided by the (co-) supervisors and their group members. The student is furthermore encouraged to attend relevant postgraduate courses and to present their results at national and international conferences. Furthermore, there is the possibility to gain experience with small mammal trapping and handling at the field site in Switzerland.   


Fig.1 A juvenile snow vole, about to be released after having been marked, weighed and measured.


Fig.2 The study site, located in the Swiss Alps at 2000m.



References / Background reading list

Bonnet, T. & Postma, E. 2017. Successful by Chance? The Power of Mixed Models and Neutral Simulations for the Detection of Individual Fixed Heterogeneity in Fitness Components. The American Naturalist 187: 60–74.
Bonnet, T., Wandeler, P., Camenisch, G. & Postma, E. 2017. Bigger is fitter? Quantitative genetic decomposition of selection reveals an adaptive evolutionary decline of body mass in a wild rodent population. PLoS Biology 15: e1002592.
Chen, N., Juric, I., Cosgrove, E.J., Bowman, R., Fitzpatrick, J.W., Schoech, S.J., et al. 2018. Allele frequency dynamics in a pedigreed natural population. bioRxiv, doi: 10.1101/388710.
Gienapp, P., Fior, S., Guillaume, F., Lasky, J.R., Sork, V.L. & Csilléry, K. 2017. Genomic Quantitative Genetics to Study Evolution in the Wild. Trends in Ecology & Evolution 32: 897–908.
Nietlisbach, P., Keller, L.F., Camenisch, G., Guillaume, F., Arcese, P., Reid, J.M., et al. 2017. Pedigree-based inbreeding coefficient explains more variation in fitness than heterozygosity at 160 microsatellites in a wild bird population. Proceedings of the Royal Society B 284: 20162763

Entry requirements

Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK.   Applicants with a Lower Second Class degree will be considered if they also have Master’s degree.  Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply.

Candidate Requirements
This project would be ideally suited to an independent, creative and highly motivated student with an interest in (quantitative and population) genetics, bioinformatics and (evolutionary and population) ecology, and who has no fear of equations and statistics. There is the possibility to do a limited amount of fieldwork, which takes place in rough terrain and is physically demanding.

All applicants would need to meet our English language requirements by the start of the  project


How to apply

In the application process you will be asked to upload several documents.  Please note our preferred format is PDF, each file named with your surname and the name of the document, eg. “Smith – CV.pdf”, “Smith – Cover Letter.pdf”, “Smith – Transcript.pdf”.

  • CV
  • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project.
  • Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim transcript if you are still studying.
  • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English.
  • Two References (applicants are recommended to have a third academic referee, if the two academic referees are within the same department/school).

Reference information
You will be asked to name two referees as part of the application process.  It is your responsibility to ensure that your two referees email their references to, as we will not make requests for references directly; you must arrange for them to be submitted by 7 January 2019

References should be submitted to us directly in the form of a letter. Referees must email their references to us from their institutional email accounts. We cannot accept references from personal/private email accounts, unless it is a scanned document on institutional headed paper and signed by the referee.

All application documents must be submitted in English. Certified translated copies of academic qualifications must also be provided.

The closing date for applications is midnight on 7 January 2019.  Interviews will be held between 4 and 15 February 2019.

If you have any general enquiries about the application process please email  Project-specific queries should be directed to the supervisor.

Data Sharing
During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

  • the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
  • administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.


Application deadline:7th January 2019
Value:£14,777 per annum for 2018-19
Duration of award:per year
Contact: PGR Enquiries