Applications are open for the 2027 Martingale Scholarships, providing postgraduate opportunities for students interested in advanced study and research in Artificial Intelligence.
For Artificial Intelligence, Martingale currently highlights eligible Master’s and PhD programmes at four leading UK universities:
- University of Cambridge
- University of Edinburgh
- University of Oxford
- University College London
The programmes span some of the fastest-growing areas of technology and research, including:
- Artificial Intelligence
- Machine Learning
- Computer Science
- Data Science
- Robotics
- Natural Language Processing
- Computer Vision
- Computational Neuroscience
- AI for Healthcare
- Responsible AI
- Autonomous Systems
Martingale states that applications for courses starting in 2027 are open now and will close on:
18 October 2026.
The Foundation also confirms an important change for the current AI scholarship programme: XTX Markets is now supporting Martingale Master’s and PhD scholarships in AI. The previous Google DeepMind AI Master’s Scholarships were delivered in partnership with Martingale from 2024 through 2026.
Martingale AI Scholarships 2027 Overview
| Detail | Information |
|---|---|
| Scholarship | Martingale Scholarships |
| Academic Area | Artificial Intelligence |
| Study Levels | Master’s and PhD |
| Country | United Kingdom |
| 2027 AI Partner | XTX Markets |
| Previous AI Partner | Google DeepMind, delivered with Martingale 2024–2026 |
| Featured AI Universities | Cambridge, Edinburgh, Oxford and UCL |
| Applications | Open |
| Course Start | 2027 |
| Scholarship Deadline | 18 October 2026 |
| Major Fields | AI, Machine Learning, Computer Science, Robotics, Data Science and related areas |
What Are the Martingale AI Scholarships?
The Martingale Foundation supports postgraduate students pursuing advanced study in strategically important academic fields.
Artificial Intelligence is one of those areas.
Martingale describes AI as a rapidly expanding field with the potential to transform society and drive advances in science and technology.
The Foundation specifically points to applications including:
- Healthcare
- Drug discovery
- Climate-change challenges
- Science
- Technology
It argues that advanced AI skills are increasingly valuable in both academia and the workforce.
Why This Scholarship Opportunity Matters
Opportunities Feed Analysis
One of the strongest aspects of the Martingale AI opportunity is the breadth of postgraduate programmes represented.
Applicants are not restricted to one narrow definition of artificial intelligence.
Depending on their academic background and research interests, they can explore areas ranging from:
machine learning and natural language processing
to:
robotics, healthcare AI, computational neuroscience, theoretical computer science and responsible AI.
This makes the programme relevant to applicants coming from several technical and quantitative backgrounds rather than only students whose previous degree was explicitly titled “Artificial Intelligence.”
Applicants must, however, check the individual admission requirements of the specific university programme they want to pursue.
Which Universities Offer Martingale AI Opportunities?
The current Martingale Artificial Intelligence page identifies:
University of Cambridge
University of Edinburgh
University of Oxford
University College London
as its featured AI universities.
Each university offers a different mix of Master’s and doctoral programmes.
University of Cambridge AI Programmes
Cambridge offers several relevant postgraduate routes.
MPhil in Human-Inspired Artificial Intelligence
This is a:
9-month programme
focused on developing AI that is:
- Human-centred
- Human-compatible
- Responsible
- Socially beneficial
- Globally beneficial
Students explore interdisciplinary AI research while developing tools for tackling practical research challenges.
The programme also addresses technical, ethical and human dimensions of artificial intelligence.
MPhil in Advanced Computer Science
This nine-month programme develops advanced computer-science research skills.
Students choose taught modules from a range of areas and undertake an independent research project.
Available subject areas can include topics such as:
- Natural language processing
- Networking
- Systems
- Advanced computer science theory
Students also receive research-skills training.
MPhil in Machine Learning and Machine Intelligence
This is one of the strongest options for applicants specifically targeting AI and machine learning.
The programme lasts:
11 months
and includes four specialist pathways:
- Machine Learning
- Speech and Language Processing
- Computer Vision and Robotics
- Human-Computer Interaction
The course aims to provide state-of-the-art knowledge in machine learning and machine intelligence while preparing graduates for both industry leadership and doctoral research.
MPhil in Data Intensive Science
This approximately ten-month programme provides advanced training in:
- Statistical analysis
- Machine learning
- Research computing
- Data-intensive research
Students learn how to design and implement data-analysis pipelines for increasingly complex datasets.
The programme also develops data-science and algorithm-building skills applicable across science, health and economic research.
MPhil in Scientific Computing
Cambridge also lists Scientific Computing.
The programme provides postgraduate education in areas including:
- High-performance computing
- Advanced algorithms
- Numerical simulation
- Scientific computing research
Cambridge PhD Opportunities
Martingale also lists doctoral study at Cambridge.
PhD in Human-Inspired Artificial Intelligence
Research areas include:
- Human-level AI
- Social and interactive AI
- Cognitive AI
- Creative AI
- Health AI
- Global AI
- Responsible AI
The programme combines technical AI research with human, ethical, applied and industrial perspectives.
PhD in Computer Science
Cambridge’s Computer Science PhD normally involves:
three to four years of full-time research
on an agreed research topic under academic supervision.
University of Edinburgh AI Programmes
Edinburgh provides both taught and research routes.
MSc Artificial Intelligence
The programme provides fundamental knowledge and practical skills for designing, building and applying AI systems.
Its interdisciplinary foundations draw on areas including:
- Neuroscience
- Cognitive science
- Linguistics
- Mathematics
Edinburgh PhD Opportunities
PhD in Foundations and Applications of Artificial Intelligence
Research includes areas such as:
- Knowledge representation
- Reasoning
- Autonomous systems
- Multi-agent systems
- Social computation
- Web semantics
- Fairness
- Accountability
- Transparency
- AI safety
The research combines theoretical AI with applied work.
PhD in Machine Learning, Computational Neuroscience and Computational Biology
This programme brings together three major research areas:
- Machine learning
- Computational neuroscience
- Computational biology
Machine-learning research includes probabilistic methods for identifying patterns and structure in data, with applications across areas such as:
- Astronomy
- Health sciences
- Computing
PhD in Theory and Foundations of Computer Science
Another Edinburgh route includes research in:
- Algorithms
- Complexity
- Cryptography
- Databases
- Logic
- Programming languages
- Quantum computing
- Security
- Privacy
- Software modelling
- Verification
University of Oxford AI Programmes
Oxford offers several programmes relevant to AI and computer science.
MSc in Autonomous Robotics
This programme focuses on creating robots capable of operating independently in real-world environments.
Topics include:
- AI
- Machine learning
- Robot fabrication
- Path planning
- Motion generation
- Mapping
- State estimation
- Sustainable robotics
Students combine research-led teaching with practical training.
MSc in Mathematics and Foundations of Computer Science
This interdisciplinary programme sits between:
pure mathematics and theoretical computer science.
Topics can include:
- Algebra
- Number theory
- Combinatorics
- Logic
- Computational complexity
- Concurrency
- Quantum computing
Students also complete a dissertation.
MSc in Advanced Computer Science
Oxford’s Advanced Computer Science programme combines theory and practice.
It is particularly relevant to graduates from:
- Computer science
- Mathematics
and culminates in an academic project allowing students to pursue a specialist interest.
Oxford Doctoral Opportunities
DPhil in Autonomous Intelligent Machines and Systems
The programme combines:
- Theoretical foundations
- Systems research
- Academic training
- Industry-initiated projects
with a focus on autonomous intelligent systems.
DPhil in Computer Science
Oxford’s Computer Science DPhil is an advanced research degree requiring an original contribution to knowledge.
Students work with specialist researchers and can undertake interdisciplinary research involving multiple research themes or industry collaborators.
University College London AI Programmes
UCL has one of the broadest selections of AI-related Master’s programmes on the Martingale page.
Machine Learning MSc
Students can specialise in different areas of machine learning.
The programme includes opportunities to study modules connected with the:
Gatsby Computational Neuroscience Unit
and:
Google DeepMind.
Importantly, the presence of Google DeepMind-related modules at UCL should not be confused with the funding partner for the 2027 Martingale scholarship.
Artificial Intelligence for Sustainable Development MSc
This programme combines technical AI with:
- Environmental issues
- Humanitarian challenges
- Sustainable development
It may particularly appeal to applicants who want to use AI for social-impact applications.
Computational Statistics and Machine Learning MSc
The programme combines advanced knowledge in:
- Machine learning
- Statistics
and includes opportunities involving modules connected to major UCL research centres.
Artificial Intelligence for Biomedicine and Healthcare MSc
This interdisciplinary programme focuses on the potential of AI to transform:
- Biomedicine
- Healthcare
Students develop advanced technical skills for designing AI-powered healthcare and biomedical solutions.
Robotics and Artificial Intelligence MSc
The programme combines:
- Computer Science
- Artificial Intelligence
- Electronic Engineering
- Mechanical Engineering
with theoretical and hands-on training in intelligent robotics.
Data Science and Machine Learning MSc
Students can study topics including:
- Artificial intelligence
- Deep learning
- Digital finance
- Probabilistic modelling
Artificial Intelligence and Data Engineering MSc
This one-year programme develops advanced skills in:
- Software engineering
- Machine learning
- Data engineering
with an emphasis on designing, building, deploying and managing real-world AI systems.
UCL Computer Science MPhil/PhD
UCL also lists its four-year Computer Science research programme.
Students conduct advanced research under academic supervision and can prepare for careers in either:
- Academia
- Industry
Which Programme Could Be Best for You?
Opportunities Feed Assessment
The variety of programmes means applicants should choose according to their existing background and long-term goals.
| Interest | Programmes Worth Exploring |
|---|---|
| Core Machine Learning | Cambridge MPhil Machine Learning and Machine Intelligence, UCL Machine Learning MSc |
| NLP | Cambridge Machine Learning and Machine Intelligence |
| Computer Vision | Cambridge Machine Learning and Machine Intelligence |
| Robotics | Oxford Autonomous Robotics, UCL Robotics and AI |
| Healthcare AI | UCL AI for Biomedicine and Healthcare |
| Responsible/Human-Centred AI | Cambridge Human-Inspired AI |
| AI for Social Impact | UCL AI for Sustainable Development |
| Data Science | Cambridge Data Intensive Science, UCL Data Science and Machine Learning |
| AI Research Career | Cambridge, Edinburgh, Oxford and UCL doctoral programmes |
| Theoretical Computer Science | Oxford Mathematics and Foundations of CS, Edinburgh Theory and Foundations |
| Computational Neuroscience | Edinburgh Machine Learning/Computational Neuroscience programme |
This comparison is an Opportunities Feed interpretation based on the programme descriptions supplied by Martingale.
Who Should Consider Applying?
The opportunity could be particularly relevant to academically strong students interested in postgraduate research or advanced technical careers involving:
- Artificial intelligence
- Machine learning
- Computer science
- Mathematics
- Robotics
- Data science
- Computational sciences
However, applicants must check the Martingale scholarship eligibility requirements and the separate admission requirements for their chosen university course.
Being interested in AI alone does not guarantee eligibility.
Important Google DeepMind Clarification
Applicants may encounter older articles referring to:
Google DeepMind AI Master’s Scholarships through Martingale.
Those articles need to be interpreted carefully for the 2027 cycle.
Martingale states that the Google DeepMind AI Master’s Scholarships were founded in 2017 and delivered with Martingale between:
2024 and 2026.
For the current programme:
XTX Markets is now supporting Master’s and PhD Scholarships in AI.
Therefore, applicants should not describe the current 2027 opportunity as a Google DeepMind scholarship unless a specific university or scholarship page explicitly states otherwise.
How Competitive Is the Scholarship?
Opportunities Feed Assessment
These scholarships should be treated as competitive because they provide access to postgraduate study at major UK research universities in highly sought-after areas such as AI and machine learning.
However, the supplied source does not provide:
- Number of applications
- Number of 2027 AI scholarships
- Acceptance rate
- Selection probability
Those figures should not be invented.
How to Improve Your Chances
Applicants should first identify the programme that most closely matches their academic preparation rather than simply choosing the most recognizable university.
For example, someone with substantial machine-learning experience might build a stronger case for a specialised machine-learning programme than for an unrelated AI pathway.
Applicants can also strengthen their profile by clearly demonstrating relevant:
- Academic performance
- Research experience
- Programming experience
- Quantitative skills
- Technical projects
- Research interests
These are Opportunities Feed recommendations rather than additional eligibility requirements published on the supplied AI page.
Application Mistakes to Avoid
Applicants should avoid:
- Calling the 2027 awards Google DeepMind scholarships
- Assuming every AI programme has identical admission requirements
- Applying to a course without checking its academic prerequisites
- Treating scholarship eligibility and university admission as the same process
- Assuming all listed courses have identical durations
- Missing the 18 October scholarship deadline
- Waiting until university application deadlines before investigating Martingale
- Inventing a scholarship stipend amount that is not stated on the supplied AI page
- Assuming admission automatically guarantees scholarship funding
Application Deadline
Applications for the:
2027 Martingale Scholarships
are currently open.
The deadline for courses beginning in 2027 is:
18 October 2026.
Applicants should check the official application page promptly because individual university programmes may operate separate admissions processes and deadlines.
Frequently Asked Questions
Are Martingale Scholarships open for 2027?
Yes. The Foundation states that applications for the 2027 Martingale Scholarships are open.
When is the deadline?
18 October 2026.
Are Artificial Intelligence scholarships available?
Yes.
Are Master’s programmes included?
Yes. The AI page lists multiple Master’s programmes.
Are PhD programmes included?
Yes. Multiple PhD and doctoral programmes are listed.
Which universities offer the listed AI programmes?
The current AI page features Cambridge, Edinburgh, Oxford and UCL.
Is Google DeepMind funding the 2027 Martingale AI scholarships?
The supplied page says Google DeepMind’s AI Master’s Scholarships were delivered in partnership with Martingale from 2024–2026. It states that XTX Markets is now supporting Master’s and PhD scholarships in AI.
Can I study machine learning?
Yes. Several listed programmes focus directly on machine learning.
Are robotics programmes included?
Yes. Oxford and UCL have relevant robotics programmes on the supplied page.
Can I study AI for healthcare?
Yes. UCL’s Artificial Intelligence for Biomedicine and Healthcare MSc is among the listed programmes.
Is Natural Language Processing included?
Cambridge’s Advanced Computer Science programme includes NLP topics, while the Machine Learning and Machine Intelligence MPhil includes a Speech and Language Processing pathway.
Can I study computer vision?
Yes. Cambridge’s Machine Learning and Machine Intelligence programme includes a Computer Vision and Robotics pathway.
Does the scholarship page specify an acceptance rate?
No.
Does the supplied AI page specify one universal stipend amount?
No. Applicants should not invent or assume a particular cash amount from this source.
Opportunities Feed Verdict
The Martingale AI Scholarships 2027 deserve particular attention from students interested in advanced AI study because the Foundation’s current course portfolio covers considerably more than general artificial intelligence.
Applicants can explore specialist areas including:
machine learning, NLP, computer vision, robotics, healthcare AI, responsible AI, data science, computational neuroscience and theoretical computer science.
The universities represented on the AI page are:
University of Cambridge, University of Edinburgh, University of Oxford and University College London.
For the 2027 cycle, applicants should pay particular attention to two details.
First, applications are:
open now
and close on:
18 October 2026.
Second, older information about Google DeepMind should not be carried forward incorrectly. Martingale explicitly states that its Google DeepMind partnership covered the 2024–2026 period and that XTX Markets is now supporting Master’s and PhD scholarships in AI.
Students interested in applying should therefore begin by identifying the eligible programme that best matches their academic background and research goals, then review the scholarship and university-specific requirements before the October deadline.
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