Leverhulme Programme for Doctoral Training: Embark on a transformative journey with the Leverhulme Programme for Doctoral Training in Ecological Data Science at the University of Glasgow. Funded by the Leverhulme Trust, this program aims to train a new generation of data scientists equipped to address pressing environmental challenges. Students will delve into areas such as biodiversity loss, ecosystem degradation, and emerging infectious diseases, applying cutting-edge data science techniques to ecological and environmental issues.
Leverhulme Programme for Doctoral Training in Ecological Data Science – PhD Scholarships
- 🎓 Funded by the Leverhulme Trust, the program focuses on pressing issues like biodiversity loss, ecosystem degradation, and emerging infectious diseases.
- 🤖 Students receive training in cutting-edge data science techniques, such as machine learning, statistical modeling, and spatial analysis.
- 🌊 Research areas include deep learning for marine acoustic and image data, natural language processing for biodiversity loss, and machine learning with metagenomics for understanding infectious diseases.
- 📚 The program structure involves a 4-year PhD with two stages: training and rotation projects (year 1) and PhD research (years 2-4).
- 🤝 Interdisciplinary collaboration is emphasized, with students working with world-leading researchers in ecology, data science, and conservation.
- 🌐 Cohort-building activities, including induction events and an annual away day, foster a collaborative and supportive environment.
- 🎓 Entry requirements include a minimum 2.1 undergraduate degree in a relevant subject, with quantitative skills for ecology or an interest in environmental science.
Summary Table:
| University | University of Glasgow |
|---|---|
| Funding Body | Leverhulme Trust |
| Program Duration | 4 years (PhD) |
| Scholarships Available | Up to 48 months, 5 scholarships per year |
Study Area: The program’s interdisciplinary focus spans ecology, data science, and conservation, offering students the chance to work on diverse projects, including marine acoustic analysis, natural language processing for biodiversity, machine learning in metagenomics, statistical modeling of species distributions, and edge machine learning for animal monitoring.
Scholarship Description: Successful applicants will undergo a 4-year PhD program structured in two stages. The first stage involves training and rotation projects, while the second stage focuses on individual PhD research. The program emphasizes interdisciplinary collaboration, ensuring students work with world-leading researchers and undertake training in data science, ecology, and professional skills development.
Eligibility:
- Minimum 2.1 undergraduate degree in a relevant subject.
- Evidence of quantitative skills for ecology applicants or an interest in ecology for quantitative backgrounds.
- Preferred: Masters level qualification.
Required Documents:
- CV
- Quantitative skills evidence or ecology interest statement
- Undergraduate and, if applicable, Masters transcripts
How to Apply: Submit your application by 22nd March 2024. Applicants will be notified of the results by 19th April 2024.
Last Date: Don’t miss the application deadline: 22nd March 2024.
Support: Each scholarship funds up to 48 months of full-time doctoral study, including a maintenance award at UKRI base levels and £10,000 for individual research and training needs.
Timeline: Recruitment for the program starting October 2024 is ongoing. Application deadline: 22nd March 2024. Successful applicants will be notified by 19th April 2024.
International Scholarships: Over the program’s duration, 3 scholarships may be offered to international students, with an additional 3 scholarships available to students from East African Community states.
Masters Plus Scholarships: Up to 3 scholarships are available to fund students for a master’s degree before progressing to a PhD. These scholarships offer 5 years of funding, covering fees and maintenance awards for all years.
Training: The program provides diverse training activities, including courses in AI, statistical modeling, spatial ecology, and biodiversity conservation. Masterclasses in collaboration with the Centre for Data Science & AI, covering intensive 1-week courses, are also offered. Students benefit from a Professional Skills Development Framework encompassing scientific writing, communication, and career development.
