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NERC GW4+ DTP PhD studentship: Adaptations of Antarctic penguins in a rapidly changing environment

  • Full or part time
  • Application Deadline
    Monday, January 06, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

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 Universities of Bath, Bristol and Exeter and Cardiff University plus five prestigious Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology & Hydrology, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad multi-disciplinary training, designed to produce tomorrow’s leaders in earth and environmental science.


Lead Supervisor: Dr Jane Younger, University of Bath, Milner Centre for Evolution
Co-Supervisor: Dr Phil Trathan, British Antarctic Survey
Co-Supervisor: Dr Araxi Urrutia, University of Bath, Milner Centre for Evolution


In the era of anthropogenic climate change, understanding species responses to environmental shifts is a central challenge in evolutionary biology. Whether standing genetic variation can aid persistence under rapid anthropogenic climate change remains an open question, as does the role of more rapid processes such as transcriptomic flexibility. Southern Ocean penguins are sentinels of climate change and a uniquely suited field system for studying adaptation, owing to their distribution across sharp environmental gradients in one of the most rapidly changing regions on Earth. This project will build on our previous advances in understanding patterns of penguin biodiversity to conduct an in-depth study of the landscape of environment-adapted molecular variation in penguins.

The overall aim of this project is to contribute to understanding the impacts of climate change on Southern Ocean penguins by assessing how they are adapted to divergent environments now. This is a broad project with many possible lines of inquiry, and the candidate is encouraged to develop specific aims according to their own interests.

We will use genomic and functional genomic datasets for populations distributed across latitudinal gradients to investigate patterns of adaptation to divergent environments. Genomic, transcriptomic and epigenomic variation both within and among populations will be analysed. Genes under directional selection will be identified using whole genome comparisons, via window-based estimates of FST and genome wide association studies to detect polygenic selection. Differential gene expression among populations will be assessed, and gene ontology and co-expression network analyses carried out to infer the functional roles of selection candidates. A machine-learning regression tree-based approach will be used to determine whether a subset of molecular variation can be explained by environment, and which environmental variables are driving local adaptation.

The candidate will be supervised by three teams with complementary expertise in adaptation (Dr Jane Younger), penguin ecology (Dr Phil Trathan), and functional genomics (Dr Araxi Urrutia). The project is also part of a wider international collaboration with Cornell University, Woods Hole Oceanographic Institution, and the Field Museum of Natural History, and the candidate will have opportunities to interact with world experts in avian ecology and evolution.

The PhD candidate will gain a diverse skillset for a career in science, with specific training opportunities tailored according to the candidate’s career aspirations. You can expect to gain communication, public engagement, scientific writing, and project management skills, as well as technical expertise in bioinformatics, R and Python programming, comparative transcriptomics, gene network analyses, and genomics.


Applicants for a studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an area appropriate to the skills requirements of the project.

This project is ideal for anyone with interests in global change biology, evolution, population genomics, or functional genomics. If you wish to pursue a career in bioinformatics, data science, or ecological or evolutionary sciences, this project will give you the skills you need. Experience (or an interest in gaining expertise) in bioinformatics, R and/or Python programming, and statistics is highly desirable.


Enquiries relating to the project should be directed to Dr Jane Younger, .

Enquiries relating to the application process should be directed to

Candidates should apply formally using the relevant University of Bath online application form:

When completing the form, please state in the ‘Finance’ section that you wish to be considered for NERC GW4+ DTP funding and quote the project title and lead supervisor’s name in the ‘Your research interests’ section. If you wish, you may apply for more than one project within the same application but you should submit a separate personal statement for each one.

More information on how to apply may be found here:

Anticipated start date: 28 September 2020.

Funding Notes

NERC GW4+ DTP funding is for 3.5 years and is open to UK and EU applicants who have been resident in the UK since September 2017.

A studentship will provide UK/EU tuition fees, maintenance in line with the UKRI Doctoral stipend rate (£15,009 per annum, 2019/20 rate) and a generous budget for research expenses and training.


Clucas, G., Younger, J. et al. (2018). Molecular Ecology 27, 4680-4697.
Ockendon, N., ... & Urrutia, A. (2016). Molecular Ecology Resources 16, 446-458.
Wang, X., ... & Urrutia, A. (2019). Frontiers in Genetics in press.
Trathan, P. et al. (2015). Conservation Biology 29, 31-41.
Bay, R. et al. (2018) Science 359, 83-86.
Fitzpatrick, M. & Keller, S. (2015) Ecology Letters 18, 1-16.
Brauer, C. et al. (2017) Molecular Ecology 26, 6841-6856.

How good is research at University of Bath in Biological Sciences?

FTE Category A staff submitted: 24.50

Research output data provided by the Research Excellence Framework (REF)

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