• Postgraduate taught
  • MRes

Machine Learning and Big Data in the Physical Sciences

Deepen your understanding of the methodologies used in research involving large data sets.

Deepen your understanding of the methodologies used in research involving large data sets

Learn how to apply tools to real-life experimental data, guided by world-leading experts

Carry out an extended project and apply your data science skills to an area of cutting-edge physics research

Course key facts

  • Qualification

    • MRes

  • Duration

    1 year

  • Start date

    September 2024

  • Study mode


  • Fees

    • £20,550 Home

    • £40,800 Overseas

  • Delivered by

  • Location

    • South Kensington

    • White City

Minimum entry standard

  • 2:1 degree or three years of relevant work experience in appropriate quantitative disciplines.

View full entry requirements

Course overview

Further your understanding of the methodologies and toolkits used in research involving large data sets on this Master's course. 

This course is excellent preparation for a PhD place, or for a role in the expanding data science industry.

Explore how the field of physics provides a unique development ground for machine learning and artificial intelligence.

You'll examine the use of machine learning and data-science techniques in the acquisition, curation and analysis of large datasets commonplace in modern physics research.

You'll also explore how different techniques can be deployed in real research and how to apply these tools to real-life experimental data.

An extended full-time project forms the major component of this course, providing you with an opportunity to join a research team and carry out world-class research in a cutting-edge physics topic.

Learn alongside world-leading experts at Imperial and deploy the latest data science technologies to enhance your research.

Get an introduction to MRes Machine Learning and Big Data and the Physical Sciences, and hear about the experiences of our current students.


This page is updated regularly to reflect the latest version of the curriculum. However, this information is subject to change.

Find out more about potential course changes.

Please note: it may not always be possible to take specific combinations of modules due to timetabling conflicts. For confirmation, please check with the relevant department.

You’ll take all of these core modules.

For in depth information about the core modules please visit the Department of Physics web pages.

Core modules

You’ll also choose at least two optional modules from a wide selection of Physics modules. A small selection is shown here; you can see a full list of optional modules (FHEQ 6 and 7 electives) on the Department of Physics web pages.

Optional modules

You'll undertake an extended research project as the largest portion of your studies. 

Here, you will carry out original research embedded in a research group which may be jointly carried out with industry. This will demonstrate your analytics and self-management skills, as well as your capacity to undertake PhD level research.

Your work will be assessed by a written report and a poster and/or presentation of your research findings.

You can complete a project in a wide range of topics. Example topics include:

  • Identifying Low-mass Dark Matter Events
  • Optimization of X-ray Pulses
  • Detecting signals of immune evasion in Sars-Cov-2

To discuss your research topic ideas further, please contact the department using the details at the bottom of this page.

Teaching and assessment

Balance of teaching and learning


  • Independent study and research project
  • Lectures, tutorials and practicals

  • 67% Independent study and research project
  • 33% Lectures, tutorials and practicals

Teaching and learning methods

  • Person at lectern giving speech
  • Person giving seminar
  • Research group meetings
  • People collaborating and completing practical work.
    Hands-on sessions
  • Exercises and practical work
  • Computer-based sessions
  • Blackboard virtual learning environment
    Virtual learning environment
  • Individual research project
    Extended research project

Balance of assessment


  • Written examinations
  • Practical and coursework
  • Research project

  • 15% Written examinations
  • 18% Practical and coursework
  • 67% Research project

Assessment methods

  • Person completing coursework
  • A person completing a written exam
    Written examinations
  • Literature review
  • Papers from a written report
    Written reports
  • Oral examination


Entry requirements

We consider all applicants on an individual basis, welcoming students from all over the world.

How to apply

Apply online

You can submit one application form per year of entry. You can choose up to two courses.

Tuition fees

Home fee

2024 entry


Overseas fee

2024 entry


How will studying at Imperial help my career?

Chemistry research on computer screen

Prepare for a variety of roles in research, in particular areas in the physical sciences where large datasets are produced and analysed.

Computer monitor showing data

Be equipped for a data science career in industry, where machine learning solutions to data analysis and understanding are key.

Terms and conditions

There are some important pieces of information you should be aware of when applying to Imperial. These include key information about your tuition fees, funding, visas, accommodation and more.

Read our terms and conditions

You can find further information about your course, including degree classifications, regulations, progression and awards in the programme specification for your course.

Programme specifications