CG-TIC Computational Biologist / Data Scientist (Fixed Term)

The University of Cambridge is seeking a highly motivated, hard-working and professional computational biology data scientist 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 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 work as part of a team of CG-TIC research data analysts, supporting colleagues across CG-TIC in processing and analysing complex and varied datasets. The team is led by the Senior Computational Biologist, and under the direction of the CG-TIC Data Management Committee. You will be embedded within a research team within CG-TIC to fully understand their research questions and to be able to provide the analytical support they will require.,

• Collaborating with clinical and lab-based investigators in the different themes within CG-TIC to develop project-specific analysis plans.
• Carrying out analysis planning, programming and data management to ensure implementation of plans.
• Collaborating with other computational biologists in the data analytics core.
• Assisting with methodological projects, including the incorporation or development of novel methods and including collaboration 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.
• Developing oral and written dissemination of findings for meetings with collaborators or for publication as journal articles.
  
  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 ingestion, processing and 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 attention to detail, good organisational skills and an ability to quickly tap into the research questions and data and analytical needs of the research teams are key to the role., Experience in Computational Biology, Biostatistics, Statistics, Bioinformatics or a related field, with an associated First degree, Masters, or ideally PhD qualification.
• Experience in processing and analysing large biological datasets.
• Expertise in programming using at least one of R or Python.
• Excellent organisational and communication skills.
• 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.
• Capable of functioning independently and collaboratively under the overall direction of the Senior Computational Biologist and the CG-TIC Data Management Committee.
• Excellent 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.
  
  The Cambridge-GSK Translational Immunology Collaboration (https://www.gsk.com/en-gb/media/press-releases/gsk-and-cambridge-university-announce-new-five-year-collaboration-in-kidney-and-respiratory-disease/) 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 and chronic respiratory disease, affecting around 545 million people (https://www.thelancet.com/journals/lanres/article/PIIS2213-2600(20)30157-0/fulltext). The mission of the collaboration is to accelerate research and development into immune-related diseases by applying cutting-edge analytical technology and analytical expertise.