Summary
The University of Edinburgh is offering a fully funded PhD programme in Machine Learning Systems through its Centre for Doctoral Training (CDT). This programme is designed to cultivate researchers with expertise across the entire systems-ML stack, fostering a holistic understanding of the discipline. Students will gain foundational research skills in Computer Systems, Machine Learning, Hardware, Sensors and Control, Programming, Integrated Machine Learning Environments, AI Ethics, and Leadership and Entrepreneurship. The programme emphasizes real-world deployment and optimization of machine learning methods, including built-in internships and entrepreneurship training, preparing students for ethically aware technical careers and leadership roles.
Designation
PhD Student / Doctoral Researcher
Key Scholarship Details
| Scholarship Aspect | Details |
|---|---|
| Scholarship Type | Fully Funded PhD Studentship |
| Funding Coverage | Stipend, Fees, and Research Costs for 4 years |
| Number of Awards | Minimum of 10 studentships available |
| Target Entry | September 2026 |
| Eligibility | UK/EU/Non-EU citizens meeting University PhD entry requirements |
| Enhanced Stipend | Available for Home students via Government TechFirst Scheme |
| International Students | Restricted number (approx. 3 per year) |
Research Area
The PhD programme focuses on Machine Learning Systems, encompassing foundational research skills in:
- Computer Systems
- Machine Learning
- Hardware
- Sensors and Control
- Programming and Integrated Machine Learning Environments
- AI Ethics
- Leadership and Entrepreneurship
Location
The University of Edinburgh, School of Informatics, Edinburgh, Scotland, UK.
Eligibility/Qualification
Ideal candidates typically possess:
- A strong degree or higher qualification in a relevant field such as Computer Science, Mathematics, Engineering, Physical Sciences, Economics, or any other field demonstrating sufficient computing and mathematical background.
- Solid experience in programming and machine learning methods.
- Ideally, experience with deep learning environments (e.g., PyTorch) or a strong computer systems background.
As a UKRI-funded CDT, applications are open to all UK, EU, and non-EU citizens, provided they meet the University’s PhD entry requirements. However, the number of international fee status students that can be recruited is restricted (approximately 3 per year).
Scholarship Description
This fully funded PhD programme is offered by the Centre for Doctoral Training (CDT) in Machine Learning Systems at the University of Edinburgh. It provides a minimum of 10 studentships for September 2026 entry, covering a stipend, tuition fees, and research costs for four years. Home students may receive an enhanced stipend through the Government TechFirst Scheme, which includes additional requirements related to widening participation and engagement with the TechFirst programme. The programme is designed as a cohort-based experience, fostering interaction and integration among students to provide real-world experience across multiple systems, approaches, and methodologies. Significant company engagement, including internships and entrepreneurship training, is an integral part of the curriculum, preparing students to be future leaders in the field with a strong ethical awareness.
How to Apply
Candidates should refer to the CDT website for comprehensive information and detailed instructions on the application process.
Last Date for Apply
- First-stage applications deadline: 14th December 2026, 23:59
- Home applicants deadline: 15th March 2027 (pending studentship availability)
Apply Link
Apply | CDT in Machine Learning Systems | School of Informatics
