MSc Computational Biomedicine (Computational Genomics) (Online)
Learn to extract meaning from complex biomedical datasets, and apply computational biology and biomedical AI to understand human disease.
Postgraduate Diploma Computational Biomedicine (Computational Genomics) (Online)
Learn to extract meaning from complex biomedical datasets, and apply computational biology and biomedical AI to understand human disease.
Postgraduate Certificate Computational Biomedicine (Online)
Learn to extract meaning from complex biomedical datasets, and apply computational biology and biomedical AI to understand human disease.
Acquire a solid foundation in computational biology, data science and biomedical AI
Gain skills in integrating, mining, modelling, visualising, and analysing biomedical data
Develop expertise in single cell omics and network biology
Course key facts
Qualification
MSc
Duration
28 months
Start date
September 2026
Study mode
Part-time, Online
-
Fees
£16,300 Home
£26,900 Overseas
Delivered by
Location
-
Online
-
Minimum entry standard
2:1 in a relevant Biological or Biomedical Science discipline or in Clinical Medicine.
Qualification
PG Dip
Duration
20 months
Start date
September 2026
Study mode
Part-time, Online
-
Fees
£13,040 Home
£21,520 Overseas
Delivered by
Location
-
Online
-
Minimum entry standard
2:1 in a relevant Biological or Biomedical Science discipline or in Clinical Medicine.
Qualification
PG Cert
Duration
1 year
Start date
September 2026
Study mode
Part-time, Online
-
Fees
£8,150 Home
£13,450 Overseas
Delivered by
Location
-
Online
-
Minimum entry standard
2:1 in a relevant Biological or Biomedical Science discipline or in Clinical Medicine.
Course overview
Study remotely at one of the top STEM universities in the world, using innovative virtual learning environments and VR technologies.
A newly developed curriculum brings together training in the latest advances in computational biology and is delivered flexibly to suit all learners.
Alongside online lectures and training material, this course also uses novel live synchronous sessions delivered via virtual reality (VR) technologies, which enables interactions in virtual spaces between lecturers and students and provides unique learning opportunities.
You will take modules in computational biology, and specialist streams in either computational genomics or computational brain sciences, together with a six month computational research project that provides training in computational biomedicine.
The course also has strong components in applied artificial intelligence (machine and deep learning) and biomedical data science.
This course will provide you with expertise in programming, statistics, AI and data science, to enhance your employability prospects in areas relevant in computational biomedicine.
Choose your stream
- Computational Genomics (this stream)
- Computational Brain Sciences
Study remotely at one of the top STEM universities in the world, using innovative virtual learning environments and VR technologies.
A newly developed curriculum brings together training in the latest advances in computational biology and is delivered flexibly to suit all learners.
Alongside online lectures and training material, this course also uses novel live synchronous sessions delivered via virtual reality (VR) technologies, which enables interactions in virtual spaces between lecturers and students and provides unique learning opportunities.
You will take modules in computational biology, and specialist streams in either computational genomics or computational brain sciences. The course also has strong components in applied artificial intelligence (machine and deep learning) and biomedical data science.
This course will provide you with expertise in programming, statistics, AI and data science, to enhance your employability prospects in areas relevant in computational biomedicine.
Choose your stream
- Computational Genomics (this stream)
- Computational Brain Sciences
Study remotely at one of the top STEM universities in the world, using innovative virtual learning environments and VR technologies.
A newly developed curriculum brings together training in the latest advances in computational biology and is delivered flexibly to suit all learners.
Alongside online lectures and training material, this course also uses novel live synchronous sessions delivered via virtual reality (VR) technologies, which enables interactions in virtual spaces between lecturers and students and provides unique learning opportunities.
The course also has strong components in applied artificial intelligence (machine and deep learning) and biomedical data science, and will provide you with expertise in programming, statistics, AI and data science, to enhance your employability prospects in areas relevant in computational biomedicine.
Choose your stream
- Computational Genomics (this stream)
- Computational Brain Sciences
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 will complete the two modules which provide you with foundational training in data handling, programming, biostatistics, and machine learning in the first year. These are the only modules in the PG Cert option.
If you’re enrolled in the PG Dip or MSc, you will then undertake modules in either the Computational Genomics stream (this stream) or the Computational Brain Sciences stream.
Core modules
Learn the foundations of biomedical data handling and develop your skills in using Linux systems and bash scripting.
You will gain expertise in both Python and R programming languages, and learn about using high performance computing, bioinformatic workflows, and applying reproducible research techniques.
Gain the skills in biostatistics and machine learning needed for biomedical data analysis, including experience in experimental design and writing a research grant proposal.
You will learn statistical theory and application using examples from biomedical data relevant to the genomics and brain sciences streams, and develop practical expertise in building machine and deep learning skills using R or Python languages.
You will develop foundational skills in processing, analysis and interpretation of multi-omic data types, understanding of the technologies that generate these datasets, and in-depth coverage of how omic data can be used to analyse gene and epigenome regulation.
You'll also focus on the impact of variation in the coding and non-coding genome, microbial genomics and antibiotic resistance, metagenomes and microbiomes, and the impact of all these processes on human disease.
Investigate advanced computational genomic methods for multi-omic data integration, interpretation and modelling.
You will receive training in single cell technologies, and will include applied training in the processing and analysis of single cell data sets and their interpretation.
Apply a range of techniques to a specific research area on a well-defined six-month computational biology project of your choosing.
You will experience a stimulating, real-life research environment that will encourage learning through active participation.
You will complete the two modules which provide you with foundational training in data handling, programming, biostatistics, and machine learning in the first year. These are the only modules in the PG Cert option.
If you’re enrolled in the PG Dip or MSc, you will then undertake modules in either the Computational Genomics stream (this stream) or the Computational Brain Sciences stream.
Core modules
Learn the foundations of biomedical data handling and develop your skills in using Linux systems and bash scripting.
You will gain expertise in both Python and R programming languages, and learn about using high performance computing, bioinformatic workflows, and applying reproducible research techniques.
Gain the skills in biostatistics and machine learning needed for biomedical data analysis, including experience in experimental design and writing a research grant proposal.
You will learn statistical theory and application using examples from biomedical data relevant to the genomics and brain sciences streams, and develop practical expertise in building machine and deep learning skills using R or Python languages.
You will develop foundational skills in processing, analysis and interpretation of multi-omic data types, understanding of the technologies that generate these datasets, and in-depth coverage of how omic data can be used to analyse gene and epigenome regulation.
You'll also focus on the impact of variation in the coding and non-coding genome, microbial genomics and antibiotic resistance, metagenomes and microbiomes, and the impact of all these processes on human disease.
Investigate advanced computational genomic methods for multi-omic data integration, interpretation and modelling.
You will receive training in single cell technologies, and will include applied training in the processing and analysis of single cell data sets and their interpretation.
You will complete the two modules which provide you with foundational training in data handling, programming, biostatistics, and machine learning in the first year. These are the only modules in the PG Cert option.
Core modules
Learn the foundations of biomedical data handling and develop your skills in using Linux systems and bash scripting.
You will gain expertise in both Python and R programming languages, and learn about using high performance computing, bioinformatic workflows, and applying reproducible research techniques.
Gain the skills in biostatistics and machine learning needed for biomedical data analysis, including experience in experimental design and writing a research grant proposal.
You will learn statistical theory and application using examples from biomedical data relevant to the genomics and brain sciences streams, and develop practical expertise in building machine and deep learning skills using R or Python languages.
Teaching and assessment
Balance of teaching and learning
Key
- Lectures, seminars and group work
- Research project and independent study
- 22% Title 1 goes here
- 78% Title 2 goes here
Teaching and learning methods
-
Virtual learning environment
-
Online lectures and learning materials
-
Presentations
-
Guest lectures
-
Group work
-
Independent study
-
Flipped classroom (Team-based learning)
-
Online practical sessions
-
Online workshops
Balance of assessment
Key
- Coursework
- Exams
- Research Project
- 50% Title 1 goes here
- 10% Title 2 goes here
- 40% Title 3 goes here
Assessment methods
-
Presentations
-
Grant writing exercise
-
Online exams
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-
Lab reports
-
Research dissertation
-
Literature review
Balance of teaching and learning
Key
- Lectures and group teaching
- Practical Sessions, workshops, demonstrations
- Independent Study
- 17% Title 1 goes here
- 13% Title 2 goes here
- 70% Title 3 goes here
Teaching and learning methods
-
Virtual learning environment
-
Online lectures and learning materials
-
Presentations
-
Guest lectures
-
Group work
-
Independent study
-
Flipped classroom (Team-based learning)
-
Online practical sessions
-
Online workshops
Balance of assessment
Key
- Programming and data analysis assignments and exams
- Team-based learning
- Literature review, grant-writing assignments and workshop reports
- 57% Title 1 goes here
- 8% Title 2 goes here
- 35% Title 3 goes here
Assessment methods
-
Presentations
-
Grant writing exercise
-
Online exams
-
Lab reports
-
Literature review
Balance of teaching and learning
Key
- Lectures and group teaching
- Practical Sessions, Workshops, Demonstrations
- Independent Study
- 17% Title 1 goes here
- 13% Title 2 goes here
- 70% Title 3 goes here
Teaching and learning methods
-
Virtual learning environment
-
Online lectures and learning materials
-
Presentations
-
Guest lectures
-
Group work
-
Independent study
-
Flipped classroom (Team-based learning)
-
Online practical sessions
-
Online workshops
Balance of assessment
Key
- Programming and data analysis assignments and exams
- Team-based learning
- Literature review, grant-writing assignments and workshop reports
- 75% Title 1 goes here
- 10% Title 2 goes here
- 15% Title 3 goes here
Assessment methods
-
Presentations
-
Grant writing exercise
-
Online exams
-
Lab reports
-
Literature review
Entry requirements
We consider all applicants on an individual basis, welcoming students from all over the world.
Technology and equipment requirements for Live Synchronous sessions and Virtual Reality use
- Wi-Fi requirements: At least 50 Mbps, 100+ Mbps recommended for a smooth experience.
- Headsets and controllers: Where possible, the college will provide a single VR headset (Meta Quest 3 or another suitable device) for students enrolled in all Computational Biomedicine course levels (PGCert, PGDip, MSc).
- There may be countries where shipping or ordering of Meta headsets may not be possible. While the headsets are expected to work in most countries (and we will do our best to ship them to non-supported countries), Meta Quest 3 support will only be available in the 25 countries specified by them.
- If you are studying in a country where there may be limitations to the uses of the VR hardware and software, those sessions will be streamed simultaneously via Microsoft Teams and will also be recorded so they can be accessed via traditional digital delivery.
- Meta account: A Meta account will be required to use VR headsets.
How to apply
Apply online
You can submit one application form per year of entry. You can choose up to two courses.
This course can be taken in progressional levels of study:
- PG Certificate (PG Cert)
- PG Diploma (PG Dip)
- MSc
Each level of study has its own entry point; you can apply to any level in the first instance but we recommend you apply for the award with which you wish to exit.
Read more about Postgraduate Certificate, Diploma and MSc degrees
Consider which stream is right for you, according to your career aims and research interests.
When applying via our application portal My Imperial, choose the appropriate stream at the start of the application process:
- Computational Biomedicine (Computational Genomics) (Online)
- Computational Biomedicine (Computational Brain Sciences) (Online)
If an offer of admission is made, it will correspond to a specific pathway. Switching streams is only possible under certain conditions.
There is no application fee for Postgraduate Certificates, Postgraduate Diplomas, or courses such as PhDs and EngDs.
If you are applying for a Master’s course, you will need to pay an application fee before submitting your application.
The fee applies per application and not per course.
The application fees for postgraduate courses are:
- £90 for all Master's applications, excluding those to Imperial Business School
- £125 for MSc applications to Imperial Business School
- £150 for MBA applications to Imperial Business School
If you are facing financial hardship and are unable to pay the application fee, we encourage you to apply for our application fee waiver.
Find out more about how to apply for a Master's course, including references and personal statements.
An ATAS certificate is not required for students applying for this course.
Fees and funding
Online - Home
MSc
£16,300 total fee
Top-up fee from the PG Dip: £3,260
PG Dip
£13,040total fee
Top-up fee from the PG Cert: £4,890
PG Cert
£8,150total fee
You should expect and budget for your fees to increase each year.
Your fee is based on the year you enter the university, not your year of study. This means that if you repeat a year or resume your studies after an interruption, your fees will only increase by the amount linked to inflation.
Find out more about our tuition fees payment terms, including how inflationary increases are applied to your tuition fees in subsequent years of study.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
If you're a UK national, or EU national with settled or pre-settled status under the EU Settlement Scheme, you may be able to apply for a Postgraduate Master’s Loan from the UK government, if you meet certain criteria.
The maximum value of the loan is £12,858 for courses starting on or after 1 August 2025.
The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
Please note:
- The loan is only available if you’re studying a full Master’s course from the start.
- If you start on a Postgraduate Certificate (PG Cert) or Postgraduate Diploma (PG Dip) and later move on to the Master’s, you won’t be eligible for this loan.
Online - Overseas
MSc
£26,900 total fee
Top-up fee from the PG Dip: £5,380
PG Dip (online)
£21,520total fee
Top-up fee from the PG Cert: £8,070
PG Cert (online)
£13,450total fee
You should expect and budget for your fees to increase each year.
Your fee is based on the year you enter the university, not your year of study. This means that if you repeat a year or resume your studies after an interruption, your fees will only increase by the amount linked to inflation.
Find out more about our tuition fees payment terms, including how inflationary increases are applied to your tuition fees in subsequent years of study.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
If you're a UK national, or EU national with settled or pre-settled status under the EU Settlement Scheme, you may be able to apply for a Postgraduate Master’s Loan from the UK government, if you meet certain criteria.
The maximum value of the loan is £12,858 for courses starting on or after 1 August 2025.
The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
Please note:
- The loan is only available if you’re studying a full Master’s course from the start.
- If you start on a Postgraduate Certificate (PG Cert) or Postgraduate Diploma (PG Dip) and later move on to the Master’s, you won’t be eligible for this loan.
Scholarships
View all scholarshipsSearch our scholarships
Value per award
- Varies
Who it's for
- Search our full list of scholarships and bursaries
Search our scholarships
Value per award
- Varies
Who it's for
- Search our full list of scholarships and bursaries
How will studying at Imperial help my career?
Acquire transferable skills relevant to a career in programming, statistics, machine learning and AI, data analysis, data handling and modelling.
Develop the expertise to pursue research positions academic research institutes and university research laboratories, government research agencies, clinical informatician in the NHS.
Opportunities in industry include life science and biomedical start-ups, drug discovery and development, and companies specialising in pharmaceuticals, sequencing and biotechnology, and data/AI technology.
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Graduates will also be ready for PhD programmes in computational biology, bioinformatics, biomedical data science, genomics and neuroscience.
Further links
Contact the department
Email: s.samarajiwa@imperial.ac.uk
Course Director: Dr. Shamith Samarajiwa, Associate Professor in Genomics
Visit the Department of Metabolism, Digestion and Reproduction website.
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Register your interest
Stay up to date on news, events, scholarship opportunities and information related to this course.
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Events, tasters and talks
Meet us and find out more about studying at Imperial.
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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.
You can find further information about your course, including degree classifications, regulations, progression and awards in the programme specification for your course.
Programme specifications