The University of Cambridge is seeking a highly motivated, organised and initiative-focused computational biologist to join a team of clinical, immunological and computational researchers within CG-TIC. The role will facilitate cutting-edge scientific studies by providing expertise in biostatistics and informatics, guiding clinical investigators in research methods and contributing to the work of a team of data scientists. 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 mission of the collaboration is to accelerate research and development into immune-related diseases by applying cutting edge analytical technology and analytical expertise. Who you'll be working with The role is based in the Department of Medicine, working with clinical and scientific researchers from CG-TIC who are based primarily in the Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID) and the Victor Phillip Dahdaleh Heart & Lung Research Institute (HLRI). CG-TIC also incorporates clinician researchers from the nearby Addenbrooke's and Royal Papworth Hospitals, and our partners at GSK. You will be part of a growing team of CG-TIC computational biologists and data scientists, collaborating with colleagues across CG-TIC in processing and analysing complex and varied datasets. You will work under the guidance of Prof. Eoin McKinney, Professor of Clinical Autoimmunity, who, in addition to leading one of the CG-TIC research projects, oversees data analytical approaches within CG-TIC. What you'll be working on 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) and Electronic Healthcare Record data. As well as data analysis, 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 will require attention to detail, good organisational skills and an ability to quickly understand and identify emerging research questions. Areas you'll be working in - Collaborating with clinical and lab-based investigators in the different themes within CG-TIC to develop project-specific analysis plans. - Applying a range of analytical techniques to bulk and single cell data and to integrative multi-omics datasets. - Developing existing and novel techniques, including machine learning. - Opportunities to collaborate with researchers in the Cambridge Centre for Artificial Intelligence in Medicine. - Working with partners at GSK, sharing approaches to data analysis, and ensuring that the needs of all partners in the collaboration are met. - Preparing presentations and written work for meetings with collaborators and for publication as journal articles. Experience required for the role - Experience in Computational Biology, Biostatistics, Statistics, Bioinformatics or a related field, with an associated Masters, or ideally PhD, qualification. - Experience of processing and analysing large biological datasets. - Expertise in programming using at least one of R or Python. - Experience in single cell data analyses and integrative multi-omics approaches is strongly desired. - A background in immunology and experience working with clinical trial data would be very useful. - Excellent organisational skills: able to function independently, but with a strong collaborative mindset. - Excellent oral and written skills with the ability to communicate technical information to both specialist and non-specialist audiences, in person and remotely. - Skilled in descriptive analysis, data modelling and graphic interfaces. - Demonstrated expertise in analytical and statistical tools. 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. Informal enquiries regarding this position are strongly encouraged. Please contact Prof Eoin McKinney (efm30@cam.ac.uk). Fixed Term: The funds for this position are available for two years in the first instance, with expectation of funding for five years. Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online. Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please include details of your referees, including email address and phone number, one of which must be your most recent line manager. Closing date: 20th August 2025 Interview date: To be confirmed Please quote reference RC45882 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. Further information • Further Particulars (RC45882) Apply online