Our MRes AI ML promotes transdisciplinary excellence

Contact details

For further enquiries about the MRes in AI and Machine Learning programme, please email us at MRes AI and ML Admissions

We are excited to offer this new research training programme for graduates who want to become Artificial Intelligence researchers and innovators. If you are enthusiastic to become an Artificial Intelligence researcher and innovator who would want to learn to develop novel and innovative AI for a custom problem, then this programme is for you.

With artificial intelligence now embedded in many areas of business and public service, people are needed who combine theoretical grounding in AI with the ability to imagine, lead and deliver Research & Development (R&D) projects that meet regulatory and real-world performance expectations. This MRes programme gives the opportunity to gain these skills, for a wide range of industries and careers, and we offer projects in various domains such as health, business and finance, communications, and energy / product supply systems.

The MRes programme is a one-year, full-time programme leading to the MRes award. It is designed to provide focussed AI training and a high-level supervised research project that will result in developing high-level analytical skills and a broad range of competences. The MRes also involves taught-module lectures and assessments in the first and second terms, combined with initial work on the main project, followed by full-time work on the project until 30 September, with the individual MRes thesis being submitted towards the end. The research project is normally supervised by one AI expert, and often co-supervised with an expert in an application area.  Some students may also have a co-supervisor from industry. MRes award holders would be able to, for example:

  • Apply broad knowledge of state-of-the-art AI and machine learning to critically assess the strengths and weaknesses of a range of research and innovation approaches. 
  • Apply the principles of the law as well as understanding of responsible research and innovation, data protection, ethics and bias relevant to AI research and innovation. 
  • Create software for advanced AI and machine learning using appropriate computing languages (e.g. Python) and frameworks (e.g. PyTorch, Tensorflow). 
  • Identify key advances, uncertainties and opportunities in AI methods and the evidence on organisational, business and human factors for applications.

The deadline for applications will close on the 10th of June.

Work in progress....

How do I apply?

We are inviting applications from students who are enthusiastic and strongly motivated by research and development work in AI methods and/or AI applications for various areas of business and public services in a multidisciplinary setting and welcome students from all over the world and consider all applicants on an individual basis. 

The Department values diversity and equality and is committed to providing an inclusive environment in which all students can thrive, and we particularly encourage applications from women, disabled and Black, Asian and Minority Ethnic applicants, who are currently under-represented in the sector. Our students will be registered in the Department of Computing, which is also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Two Ticks Employer, and is working in partnership with GIRES to promote respect for trans people.

Only students who have been matched with a project and have met all relevant requirements, would be able to be considered for an offer. 

Entry requirements
The minimum academic requirement is normally a first-class degree in a relevant scientific or technical discipline, such as computer science, engineering, mathematics, statistics or physics. Graduates with other natural science degrees (e.g. life sciences, chemistry) who have strong mathematical or computing grounding and programming skills may also be considered.

If you have a non-UK degree, please check the College minimum entry requirements, but note that the entry requirements to this MRes programme are normally higher than College minimum requirements.

Non-native English speakers must also meet the College English requirements. You do not have to take an English test before applying, but need to pass an approved test before starting the programme.

Please note that meeting the minimum academic requirement does not guarantee you would be made an offer of admission

Application deadlines
The provisional deadline is 30 April 2023.
If places are left, the provisional deadlines would be 31 May 2023 (for international applicants who need to apply for ATAS) and 31 June 2023 (for Home/UK applicants).

Please note, however, that we reserve the right to close applications earlier, if necessary, before these dates. We therefore recommend applying sooner rather than later. It typically takes 3-4 months after receiving your complete application to confirm the outcome of your application or interview, via the College application system.

Before you apply
Before you apply for this programme, you need to decide on a research area and ideally on a supervisor you would like to work with. Please visit our Projects page further below which is intended to help you identify a supervisor or a project. However, you need to submit a formal application to the Imperial College application system first before contacting a prospective supervisor.

Your research interest and/or supervisor choice should be explained in your personal (motivation) statement. You must list at least one project or supervisor in your personal statement when you apply. If you have more than one choice, please include information on the order of your preference(s).

Please ensure that your application is complete; only complete applications will be passed on for review. This means that we should ideally be in receipt of both references your transcript of results, CV and personal (motivation) statement before we can begin to view and assess an application. We strongly recommend that you track whether their references have been sent and be pro-active in chasing their referees if necessary.

Please note that there is no guarantee that your preferred project or supervisor will be available.

Apply online
Please apply online via our MRes AI and Machine Learning page of the Imperial postgraduate prospectus.

Please ensure you read the information in paragraph above 'Before you apply'.

There is no application fee for MRes programmes. 

What happens after I apply?
Your application will be reviewed by the MRes Programme Admissions tutor and the proposed MRes project supervisor(s). The selection process is continuous from mid November, typically until available projects are allocated, which could be before any closing dates.

Students who meet the minimum entry requirements are required to complete the MRes admissions tests. The MRes admissions tests typically include questions on Maths, programming and AI concepts, for example. All of the tests are online tests, and the majority of the tests are multiple-choice question tests.

If the proposed project supervisor(s) wants to take your application forward, you would be invited for an interview. The outcome of your application is communicated via the College application system, typically within 4 months of receiving your complete application. If you are offered a place, you will need to fulfil any required conditions, shown in their application portal, such as for example the English language test, references, certificate of academic qualification, ATAS* etc before you can start the programme.

 *An ATAS certificate is required for all visa-nationals, with the exception of EEA/Swiss nationals and nationals of the following countries: Australia, Canada, Japan, New Zealand, Singapore, South Korea and the USA. Please find more information on our MRes AI and Machine Learning page of the Imperial postgraduate prospectus.

Competency standards
We believe in providing the widest practicable access to all of our degree programmes and would aim to make reasonable adjustments wherever possible to support your study. All applicants are asked to familiarise themselves with the Computing competency standards that all postgraduate students at the Computing Department would be expected to meet.  


As part of the application process, MRes applicants need to find/discuss possible projects with a potential supervisor(s) to ensure that there is a suitable project available for the MRes studies. 

Students should always apply through the system first before contacting any supervisors. Then, as part of the application process, MRes applicants need to find/discuss a project with a potential supervisor(s) to ensure that there is a suitable project available for the MRes studies.

Projects on offer for the 2023 intake

Belardinelli Francesco
• Imagination-based Agents for Reinforcement Learning
• Verification of Temporal Goals for Trustworthy Reinforcement Learning

Emil Lupu
• Neural Architecture Search for Robust Embedded ML Models
• Information fusion for autonomous vehicles
• Are Neuro-Symbolic Models robust to adversarial attacks?

Iddo Tzameret
Limitations on Learning Algorithms and Provability

Matthieu Komorowski
Three-dimensional Imaging Data Reconstruction to Predict Response to Prone Positioning in ARDS

Alessio Lomuscio
• Efficient custom cutting planes for neural network verification
• Verified neural network training without over-approximations

Pedro Mediano
• Learning about physics and brains with deep learning causal abstraction
• Discovering the hidden manifold of brain states with metric learning and likelihood-free inference
• Curing coma with nonlinear control theory applied to brain dynamics
• Building interpretable generative models of brain activity with physics-informed neural networks

Dario Paccagnan
Mark van der Wilk
Breaking the Train-Test Barrier: Generalization Bounds without a Test Set

Sonali Parbhoo
Identifying Medical Dead Ends In High-Risk Settings

Joram Posma
Topological machine learning to analyse metabolomic networks for idiopathic pulmonary fibrosis

Chen Qin
Deep generative model-based network for accelerated MRI reconstruction

Nicole Salomons
Reinforcement Learning for selecting a Robot's Role while Tutoring People

Thomas Heinis
Machine Learning for DNA Data Storage

Tolga Birdal
• VidStyleODE4D: Disentangled Spatio-temporal 3D Video Generation via Diffusion Models and NeuralODEs
• CP6D: Quantifying Camera Relocalization Uncertainty via Conformal Prediction
• Adiabatic Quantum Computation Assisted Artificial Intelligence

Calvin Tsay
Mixed-integer programming for trained Gaussian process models

Guang Yang
"DALL-E-CXR": A Bidirectional Synthesis for CXR reports and CXR images

Li, Yingzhen
• In-context learning vs few-shot learning: any difference?
• Make Stein’s method great again for score-based generative models

Specia, Lucia
Automated discourse analysis to distinguish between human and AI-generated language

Academics who are likely available as an MRes supervisor include:

Supervisors who are not available include Professor Francesca Toni, Professor Murray Shanahan, and Professor Andrew Davison.

Please note that the lists above are not exhaustive in that supervisors may have been allocated and then are not available anymore as the application cycle progresses.

If none of these supervisors are preferred to you, please check back for updates. You may contact the programme team at MRes AI and ML Admissions mres-ai-ml.admissions@imperial.ac.uk to enquire if your preferred supervisor is available in cycle 2023-24.


What will I study?

Core to our MRes programme is the research thesis, a substantial and major project providing an opportunity for students to apply a systematic approach to solving a substantial problem in or with AI. Furthermore, the MRes programme includes AI foundation courses, including ethics, responsible innovation and research skills training, including literature review and simulated R&D project proposal.

The programme would normally include: 
a. AI courses, including responsible innovation and ethics
b. Research skills training, including literature review and simulated R&D project proposal
c. A major independent research project and thesis

a. The AI courses will strengthen your skills in programming and AI technologies.  You will master programming for advanced AI (e.g. Python programming) and machine learning; will have taught modules in law and ethics, and a two-term series of tutorials (reading group model) looking at a wide range of state of the art AI algorithms and applications beyond your project domain.

b. To develop in-depth study and research skills, you will undertake a literature review and present a simulated R&D proposal exercise in an area related to your main project area. This will help develop your ability to independently shape and evidence a rigorous research and development plan.  You will also learn how to present a technology business case (or grant proposal) addressed to different stakeholders and audiences, and how to assess human and business perspectives.

c. The individual research project will allow to fully explore AI / ML approaches in the area that you study in-depth, with scope to learn through several cycles of development and evaluation.  Supervision and assessment will be based on progress milestones such as a poster presentation, the MRes thesis and a viva. The work on the research project will stretch over multiple terms.

You would also typically asked to complete the Imperial College programme of professional skills development courses delivered by the Graduate School, and would attend seminars and journal clubs throughout the year.

The Programme specifications of the Academic Year 2021-22 can be found here
Please note that content and/or assessment structures may change for the coming academic year.