University of Edinburgh Machine Learning Systems PhD Programme 2027 – Fully Funded
Offered by University of Edinburgh
Location
United Kingdom
Funding
Fully Funded
Study level
PhD, Graduate
Field of study
Mathematics & Statistics, Physical Sciences, Computer Science & IT
Application deadline
December 14, 2026
About This Scholarship
The University of Edinburgh in Scotland is inviting applications for its Centre for Doctoral Training (CDT) in Machine Learning Systems PhD programme for 2027 entry. The programme is designed for graduates who want to conduct advanced research at the intersection of machine learning, artificial intelligence and computer systems.
Machine learning depends not only on algorithms but also on the computing infrastructure, software, hardware and deployment methods that make those algorithms work effectively. This doctoral programme brings these areas together, preparing researchers to develop machine learning technologies that are efficient, reliable and useful in real-world settings.
The programme is based in the University's School of Informatics and brings together researchers from different disciplines. Its industry connections and interdisciplinary training provide opportunities to explore how machine learning systems can be developed and applied across sectors such as healthcare, cybersecurity, finance, electronics, high-performance computing and the creative industries.
Host institution: University of Edinburgh Programme: Centre for Doctoral Training in Machine Learning Systems Location: Edinburgh, Scotland, United Kingdom Expected entry: 2027 Study mode: Full-time, four years Funding: Fully funded studentship First-round application deadline: 14 December 2026 at 23:59 UK time
💰 Funding and Benefits
Successful candidates receive a funding package covering the principal costs associated with doctoral study.
The funding includes:
Full tuition fees: Tuition fees are covered for both UK and overseas students awarded funding through the programme.
Doctoral stipend: Financial support to help cover day-to-day living expenses during the funded period.
Research funding: Support for eligible research-related activities and expenses.
Travel funding: A research and travel grant to support relevant academic activities.
Four years of support: Funding covers four years of full-time study, subject to the programme's terms and conditions.
Structured doctoral training: Students take courses alongside their research and develop expertise across machine learning and systems.
Research supervision: Students receive guidance from supervisors and researchers associated with the programme.
Industry engagement: Opportunities to interact with industry partners and explore research challenges beyond academia.
Professional development: Training in research communication, responsible innovation, public engagement and entrepreneurship.
Important financial note: The stipend amount should be confirmed with the programme before publication as a specific figure. The funding does not cover international students' visa fees or Immigration Health Surcharge (IHS). Accommodation, food and other personal living expenses must be managed from available financial support.
🔬 Research Areas
The programme considers the wider machine learning systems landscape, including the technologies needed to build, train and deploy machine learning models.
Relevant areas may include:
Machine learning algorithms and systems optimisation
Artificial intelligence and deep learning
Computer systems and distributed computing
Computer architecture, hardware and accelerators
Software systems, compilers and programming tools
High-performance computing
Efficient and scalable machine learning
Data-intensive computing
Responsible AI and the social implications of machine learning
Practical deployment of machine learning technologies
Applicants should consult the programme's research themes and supervisor information to identify the areas that best match their interests.
✅ Eligibility Requirements
Applicants should review the official programme guidance carefully before submitting an application.
Academic qualifications
Applicants normally need a UK upper second-class honours degree (2:1), or an international equivalent, in a relevant discipline.
Relevant academic backgrounds may include:
Informatics or computer science
Artificial intelligence or machine learning
Mathematics or statistics
Physics
Engineering
Cognitive science
Another discipline supported by convincing evidence of the required academic and technical preparation
A relevant master's degree may strengthen an application, but applicants should consult the official entry requirements to establish whether their qualifications meet the programme's criteria.
Technical preparation
Applicants should be able to demonstrate suitable preparation for doctoral research in machine learning systems. Depending on their background and proposed research interests, useful experience may include programming, mathematical modelling, algorithms, data analysis, computer systems or machine learning projects.
International applicants
The first recruitment round is open to both international and UK Home applicants, subject to the programme's entry requirements and funding availability. International applicants should apply by the first-round deadline because the subsequent round is restricted to Home applicants.
Applicants from Nigeria and other countries outside the UK should check the university's international qualification guidance and English-language requirements.
English-language requirements
Applicants must meet the University of Edinburgh's English-language requirements. The university lists accepted tests and other permitted ways of demonstrating proficiency on its official programme page. Check the requirements that apply to your qualifications and circumstances before applying.
📅 Programme Structure
The full-time PhD lasts four years and combines formal training with original research.
Year 1: Foundations and research development
Students study foundational machine learning systems material, select specialised courses and undertake an introductory research project that helps establish the direction of their doctoral work.
Year 2: Advanced study and wider perspectives
Students continue their research and complete further training, including study of the social and societal context of data and technology.
Year 3: Research and external engagement
Students continue their doctoral research and will usually undertake an internship with a company or public-sector organisation, typically lasting three to six months. Alternative forms of engagement may be arranged.
Year 4: Research completion
Students concentrate on advancing and completing their research, communicating their findings and preparing their doctoral thesis, in accordance with university requirements.
The precise course selection and research plan are agreed with the relevant supervisors and programme organisers.
📝 How to Apply
Applications begin through the CDT's first-stage application process. Applicants should read the official guidance before starting.
Review the programme: Read the official Machine Learning Systems CDT website and research information to understand its aims and research themes.
Check your eligibility: Confirm that your degree and academic background meet the entry requirements.
Prepare your application information: Be ready to explain your academic background, technical preparation, research interests and reasons for applying.
Complete the first-stage application: Submit the required online form before the deadline.
Monitor your email: Applicants who progress beyond the first stage are invited to submit a full application through the university's EUCLID system.
Submit the full application: Follow the invitation and instructions carefully, including the required supporting documentation.
Respond to further requests: Check your email regularly for updates and any additional instructions from the admissions team.
Submitting the first-stage form does not guarantee an invitation to the next stage or an offer of admission.
💡 Application Tips
Demonstrate research fit. Explain why the combination of machine learning and systems research interests you, rather than discussing AI only in general terms.
Show evidence of technical ability. Describe relevant coursework, research projects, programming experience, publications or practical work where applicable.
Explain your research interests clearly. Identify a problem you would like to investigate and explain why it matters.
Highlight interdisciplinary strengths. The programme welcomes relevant backgrounds beyond computer science, so explain how your discipline prepares you for the research.
Connect your experience to the programme. Show how your previous studies or projects relate to machine learning systems.
Follow the official application guidance. Use the requested format and answer the actual questions on the form.
Apply early. Leave sufficient time to prepare your answers and resolve any application issues before the deadline.
Check international requirements. Verify degree equivalency, English-language evidence, visa costs and the financial implications of studying in Edinburgh.
⏰ Important Deadline and Selection Timeline
First-round deadline: 14 December 2026, 23:59 UK time.
According to the published recruitment timeline, applicants should receive the outcome of the first-stage application by 7 January 2027 at the latest. Candidates selected for the next stage are invited to submit a full university application by 21 January 2027 at 23:59.
A second round is listed for eligible UK Home applicants only, closing on 15 March 2027, subject to remaining studentship availability. International applicants should not rely on this later round.
Dates and procedures can change, so check the official deadline page before applying.
❓ Frequently Asked Questions
1. Is the Machine Learning Systems PhD fully funded?
Yes. The programme states that its funding covers tuition fees for UK and overseas students, a stipend, and research and travel funding for four years of full-time study, subject to the funding terms.
2. Can international students apply?
Yes. The first-round recruitment process is open to international applicants as well as UK Home applicants. However, funded places are limited, and admission and funding are competitive.
3. Does the funding cover international visa costs?
No. The programme states that international students must cover their visa fees and Immigration Health Surcharge separately.
4. Do I need a master's degree?
The published entry requirement refers to a UK 2:1 honours degree or an international equivalent in a relevant discipline. Check the official guidance to determine whether your particular qualifications satisfy the entry requirements.
5. Is the programme only for computer science graduates?
No. The university identifies several potentially relevant backgrounds, including informatics, computer science, AI, cognitive science, mathematics, physics and engineering. Applicants from other disciplines need to demonstrate sufficient preparation for the programme.
6. Is there an application fee?
The university's programme page states that there is no application fee for this programme.
7. Can international applicants apply in the second round?
The published recruitment guidance states that the second round is for Home applicants only. International applicants should therefore submit their applications by the first-round deadline.
8. Where can I find the official application information?
Use the university's official programme website and application-deadline page linked below. These are the authoritative sources for current eligibility criteria, application procedures and recruitment dates.
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