CG-TIC Computational Biologist/Data Scientist (Fixed Term)
CG-TIC Computational Biologist/Data Scientist (Fixed Term)
The Cambridge-GSK Translational Immunology Collaboration (CG-TIC) is a new, interdisciplinary partnership between the University of Cambridge and GSK bringing together expertise in immunology, AI and clinical development from both partners. The collaboration will focus on two disease areas: chronic kidney disease, estimated to affect 850 million people (roughly 10% of the world's population) (International Society of Nephrology) and chronic respiratory disease, affecting around 545 million people (The Lancet). The partnership is built around three key themes, involving the integration of patient phenotyping, understanding mechanisms of disease, and advancing oligonucleotide therapeutics.
The University of Cambridge is seeking a highly motivated, hard-working and professional computational biologist/clinical expert to work alongside an analytical team consisting of clinical, immunological and computational researchers within CG-TIC. The role will facilitate cutting-edge scientific studies by providing expertise in biostatistics and informatics, assisting clinical investigators in research methods and collaborating with the teams of data scientists and computational biologists.
Who you'll be working with
The role is based in the Department of Medicine, working with clinical and scientific researchers based in the Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID) and the Victor Phillip Dahdaleh Heart & Lung Research Institute (HLRI) who are part of the CG-TIC. You will work under the supervision of the project lead and the Data Management and Senior Management Committees to support colleagues across CG-TIC in processing and analysing complex and varied datasets.
What you will do
The collaboration will generate and have access to clinical and immunological data as well as many large data sets, including spectral immune phenotyping, proteomics and single cell sequencing data, both spatial and droplet. The successful candidate will join a vibrant team of academic data scientists working on a wide variety of collaborative projects in medicine involving clinical and experimental data, utilising cutting-edge tools and platforms. As well as working on ingestion, processing and analysis of data, you will be able to present your results to others in the collaboration and at conferences. You will be working with a wide range of stakeholders, and attention to detail and good organisational skills are key to the role.
What you will have
- MSc or higher degree in Computational Biology, Biostatistics, Statistics, Bioinformatics or related field.
- Experience processing and analysing large biological and health datasets, using a combination of standard libraries and bespoke methods, is strongly desired.
- Experience of programming languages including R and Python.
- Excellent organisational and communication skills.
- Experience in single cell data analyses and integrative multi-omics approaches.
- A background in immunology and experience working with clinical trial data is desirable.
- Outstanding oral and written communication skills with the ability to communicate technical information to a wide range of audiences.
- Skilled in descriptive analysis, data modelling and graphic interfaces.
- Demonstrated expertise in analytic tools.
- Experience supervising colleagues including training, mentoring and coaching.
Please look at the 'Further Particulars' for more details on the role
We support flexible and family-friendly working and are open to non-standard working patterns. While this is advertised as a full-time role, we would consider applications from candidates who are looking to work less than full-time hours and are open to applicants who live outside Cambridge but are willing to travel to Cambridge when required (at least a minimum of one day a week).
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Informal enquiries regarding this position, including expected salary, are strongly encouraged: contact Prof Eoin McKinney (efm30@cam.ac.uk).
Fixed-term: The funds for this post are available for 2 years in the first instance.
Please ensure that you outline how you match the criteria for the post and why you are applying for this role on the online Application form.
Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.
The closing date for applications is: 24/05/2026
The interview date for the role is: To be confirmed
Please quote reference RC49656 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
Key information
Department/location
Salary
£42,254-£56,535
Reference
RC49656
Category
Date published
8 May 2026
Closing date
24 May 2026
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