Biomedical Research (Data Science) MRes

  • Postgraduate taught
  • MRes

Biomedical Research (Data Science)

Interdisciplinary training in 'big data' analysis, building skills towards a career in biomedical research.

Receive interdisciplinary training in 'big data' analysis and build skills towards a career in biomedical research

Learn how to implement statistical and machine learning techniques and interpret data sets

Develop your communication, presentation and grant-writing skills across two research projects

Course key facts

Minimum entry standard

  • 2:1 in an appropriate subject

View full entry requirements

Course overview

Receive interdisciplinary training in 'big data' analysis in relation to biomolecular studies on this Master's course.

On this stream of the MRes in Biomedical Research, you'll receive core training in multivariate statistics, chemometrics and machine learning methods.

The course will build your research experience in the development and application of these methods to real-world biomedical studies.

You'll also learn to handle large-scale data from molecular phenotyping techniques such as metabolic profiling and related genomics approaches.

Two research projects are major components of this course.

These will help you develop communication, presentation and grant-writing skills, and become familiar with evaluating research reports.

Choose your stream

You have the option of choosing our general biomedical research stream, or one of eight specialisms. All of our biomedical research streams have the same course structure and each stream has its own tailored set of projects alongside a core programme of lectures, seminars and practical classes.

You should consider which stream is right for you according to your career aims and background. If an offer of admission is made, it will correspond to a specific stream. Switching streams is not possible once you have commenced your studies.

Is this stream for you?

This stream is suitable for students with a background in physical sciences, engineering, mathematics, computer science or similar field who wish to apply their numeric & computational skills to solve problems with biomedical data.

You will gain experience in analysing and modelling big data from technologically advanced techniques applied to biomedical questions.

You will perform novel computational informatics research and exercise critical scientific thought in the interpretation of results, implement and apply sophisticated statistical and machine learning techniques in the interrogation of large and complex biomedical data sets.

This stream is delivered by the Department of Metabolism, Digestion and Reproduction.

Structure

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.

Core modules

Teaching and assessment

Teaching and learning methods

  • Demonstrations and seminars
  • Workshops
  • Computing labs
  • Journal clubs
  • Blackboard virtual learning environment
    Virtual learning environment
  • Four students sitting in a tutorial
    Tutorials
  • Lab-based learning
  • ID badge for site visit or facility tour
    Facility Tours
  • Person at lectern giving speech
    Lectures
  • Debates

Balance of assessment

Key

  • Grant writing exercise
  • Research projects

  • 10% Grant writing exercise
  • 90% Research projects

Assessment methods

  • Microscope for lab work
    Laboratory-based research
  • Computer-based research
  • Oral presentation
  • Poster presentation
  • Papers from a written report
    Research reports
  • Oral assessment

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

2025 entry

£20,600

Overseas fee

2025 entry

£45,000

Scholarships

The Dean’s Master’s Scholarships

Value per award

  • £10,000

Who it's for

  • All students applying to study a Faculty of Medicine Master’s programme
Find out more

The Dr Jean Alero Thomas Scholarships

Value per award

  • Partial or full tuition fee at the Home rate

Who it's for

  • All students applying to study a Faculty of Medicine lab-based Master’s programme
Find out more

How will studying at Imperial help my career?

Strengthen your career prospects as aspiring Anaesthetists and Intensive Care physicians.

Cultivate a robust network within an inclusive Division, fostering valuable connections with academics and clinicians.

Participate in Departmental Research symposia, offering exposure, critical appraisal skills, expert engagement, and staying updated in the field.

Develop key academic skills to support your progress to PhD or medical school.

Develop essential soft skills, such as communication, teamwork, and adaptability, crucial for success in professional healthcare environments.

Get support with grant applications and publication of research findings, enriching academic and professional portfolios.

Participate in Departmental Research symposia, offering exposure, critical appraisal skills, expert engagement, and staying updated in the field.

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