Course Director:
Professor M. Sternberg

Course Co Director:
Dr Derek Huntley

Course Administrator:
Jennifer Bennett

DeepMind Scholarships in Life Sciences

This is a multidisciplinary research-based MSc course, designed for applicants with a biological, biomedical, physical, computational or mathematical background. It equips students with the necessary skills to produce effective research in bioinformatics and theoretical systems biology. After completing this course, students will have acquired an understanding of research topics is several areas of bioinformatics and theoretical systems biology.  Students will have extensive opportunity to develop substantial experience in software development.  Given the course's emphasis on software development analysis, normally we require our students to have some previous experience of computer code development. Many of our students progress to undertake PhD research at Imperial or at other intuitions in the UK and overseas. The course, which is primarily based at the South Kensington campus, has been designed and is taught by staff from the Faculties of Natural Sciences, Engineering and Medicine. Teaching is by experts in relevant fields within the College.  

 In the first term, students undertake taught courses typically providing information not covered by their first degree courses: 

    • Bioinformatics and Systems Biology - Introduction to biology; advanced tools for the
      analysis of biological data; and approaches for modelling biological systems
    • Computing - Python; an introduction to program design and command line computing in a Unix shell
    • Mathematics and statistical inference - high level algorithms and the analysis of large datasets

The remainder of the year is devoted to three full-time research projects, undertaken under the supervision of researchers at Imperial College (this may also involve collaboration with other academic centres or industry but the student must be based at Imperial College).

Please note that the information given on this web site provides a general guide to the course but precise details can alter to reflect the rapidly changing nature of the field and the research interest of the academics delivering the course.

More information

Course Structure

Autumn Term  (October - December)

In the first term, students will be provided with the supplementary information typically which will not have been covered by their previous degree courses or experience. This will be achieved through a basic specifically-designed and taught Bioinformatics (I) module and through computing and mathematics teaching.

Bioinformatics and Systems Biology I - The module covers the broad fields of molecular and cell biology together with genetics and genomics as core curriculum. The course is particularly designed for students without a first degree in the biological sciences. Lectures and material will be designed to reinforce basic concepts and to introduce more advanced issues related to bioinformatics and computational biology.

Mathematics - The basics of probability and statistics will be introduced, covering: axioms of probability, interpretations of probability, laws of probability, independence, discrete and continuous random variables, basic descriptive statistics, rudiments of estimation, basic notions of frequentist and Bayesian inference, and the descriptive analysis of large data sets. The course will also cover the use of differential equations to model biological systems.  Machine learning will be introduced.

 Computing - Programming skills and experience of UNIX/Linux. The main elements will be:

(1)Programming: Python

(2)Introduction to relational databases and SQL

(3) Associated assignments: Programming exercises will be designed to supplement the material covered and to give familiarity with UNIX/Linux environments, and with the Python language.

Bioinformatics II - There are four parts:
(1) The protein component: Principles of protein structure and function. Annotation and prediction of protein structure, function and interactions.

(2) The DNA component: DNA sequence analysis; genome assembly and annotation; expression analysis.

(3)Statistical component: statistical and population genetics

(4) Systems Biology Component: networks, biophysical modelling and mathematical modelling.

Research projects (January - September)

The research projects are designed to provide students with experience in implementing a substantive research project in Bioinformatics and to practise the skills they have learnt from the taught components of the MSc course. All projects will directly involve liaison with biologists, mathematicians, and computing specialists. All projects have a 10 -12 week duration. Students will be offered a choice of topics, and for the second and third these can be from across Imperial College including in groups located a campuses associated with hospitals. We aim for students to have a project of their choice, but this cannot be guaranteed

Project oneis a computing project, reinforcing programming skills and providing an opportunity to experience creation of code in detail.

Project two is a data analysis project which involves the students working on the statistical and computational analysis of biological or biomedical datasets in collaboration with experimental/clinical groups within Imperial College London. This should be related to ongoing research projects.

Project three is a bioinformatics and systems biology project, and provides a mechanism for use of the skills obtained during the course in a research environment. Students become part of their host laboratory within Imperial College, including associated hospitals and Silwood Park. Some of these projects contribute directly to scientific publications.

Students have plenty of opportunities to attend professional skills training run by the Graduate School MasterClass


How to Apply

Apply here

For further information email Jennifer Bennett

Links with Employers

Imperial College works closely with employers and industry, including Industrial Advisory Panels to design Master’s courses which provide graduates with technical knowledge, expertise and transferable skills and to encourage students to take internships and placements. All Master’s courses are designed with employer needs in mind with some Master’s courses accredited by Professional, Statutory and Regulatory Bodies.

Entry Requirements

Academic requirements

Applicants with a first degree in biological, physical, computational or mathematical courses, or equivalent overseas qualifications, are welcome to apply.

If your first degree is from a country other than the UK, you may find the guidelines within our Country Index helpful. Please note that these guidelines indicate the College minimum.

We particularly encourage graduates from numerical and physical sciences to join this programme.

The minimum qualification for admission is an Upper Second Class Honours (2:1) degree  from an UK academic institution or an equivalent overseas qualification.

 Extensive relevant work experience with a lower degree will be considered in special cases.

 The College also has a minimum English language requirement for postgraduate study; see more details.

 If you are in doubt about your eligibility, then do either make an enquiry or apply!

Fees and Funding