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Biological Sciences (4) Chemistry (6) Engineering (12) Environmental Sciences (13)
University of Glasgow

The Leverhulme Programme for Doctoral Training in Ecological Data Science

Based at the University of Glasgow and funded by the Leverhulme Trust, the Leverhulme Programme for Doctoral Training in Ecological Data Science will train a new generation of data scientists. The programme will equip students with the skills to tackle the most pressing environmental challenges of our time, including biodiversity loss, ecosystem degradation, and emerging infectious diseases. Students will be trained in the latest data science techniques, including machine learning, statistical modelling, and spatial analysis, and will apply these skills to a range of ecological and environmental problems.

The programme will provide students with a unique opportunity to work with world-leading researchers in ecology, data science, and conservation, and to undertake research in a range of exciting areas, including:

  • Deploying deep learning to analyze marine acoustic and image data
  • Using natural language processing to understand the drivers of biodiversity loss
  • Combining machine learning with metagenomics to understand emerging infectious diseases
  • Developing new statistical methods for modelling species distributions
  • Creating edge machine learning algorithms to monitor animal movement and behaviour
The Leverhulme Programme for Doctoral Training in Ecological Data Science

Programme Structure

The focus of the programme is on interdisciplinary training and research with students undertaking a 4-year PhD. In year 1, students will undertake a group rotation project in three of the listed projects, before selecting a single project as their PhD research. More information about the programme and the structure is available here.

Funding and eligibility

Fully funded studentships are available at the UK home rate and international rate, eligibility requirements are available here.

All applicants must have or expect to obtain a first-class degree (2.1 or equivalent) in an appropriate discipline, ecology, biology, mathematics, statistics, physics, computer science, engineering, etc.

Applicants with a background in ecology will be expected to have evidence of quantitative skills in statistics, mathematics, or programming. Applicants from a quantitative background will be expected to show an interest in ecology and environmental science.

A masters level qualification is preferred but is not an essential requirement.

How to apply

We are now accepting applications for session 2025/26. Application deadline - 7th March 2025.

To apply please use the link below. You will need the following documents to complete your application:

  • A personal statement (to include evidence of your interest in ecology and data science, your research interests, and your future aspirations)
  • An up-to-date CV
  • The transcript of your undergraduate degree
  • The transcript of your Masters degree (if applicable)
  • Two letters of reference (at least one reference should be submitted before interview)

Masters plus PhD scholarships

To promote the progression of Black students and students from low-income backgrounds in the UK, up to 3 scholarships are available over the course of the programme to fund students to undertake a master's degree before progressing to a PhD. More information is available on our website. Masters Plus Scheme applicants should complete a standard application and note their interest in the Master Plus Scheme on their cover letter, please note that this is only available to home Black students and home students from low-income backgrounds.

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Email: scieng-gradschool@glasgow.ac.uk
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