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

University of Cambridge; Cambridge; On-site; GBP 30,000 - 50,000; Part time

Job summary

An established industry player is seeking a motivated Computational Biologist/Data Scientist to join their innovative team. This role focuses on supporting groundbreaking research in immunology and chronic diseases by applying advanced analytical techniques. You will collaborate with a diverse team of researchers, contributing to the analysis of complex datasets and presenting findings to various stakeholders. This is a unique opportunity to work at the intersection of science and technology, enhancing your skills in a supportive and dynamic environment. If you're passionate about data science and its applications in healthcare, this role is perfect for you.

Benefits

Flexible working arrangements

Professional development opportunities

Access to cutting-edge technology

Qualifications

• Experience in processing and analyzing large biological datasets.
• Expertise in programming using R or Python.
• Background in immunology and clinical trial data is beneficial.

Responsibilities

• Collaborate with clinical investigators to develop analysis plans.
• Carry out data management and analysis for project implementation.
• Present results to stakeholders and at conferences.

Skills

Computational Biology

Biostatistics

Bioinformatics

R Programming

Python Programming

Data Analysis

Communication Skills

Organizational Skills

Education

First Degree in Relevant Field

Masters in Relevant Field

PhD in Relevant Field

Tools

Statistical Software

Analytic Tools

Job description

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

Join to apply for the CG-TIC Computational Biologist/Data Scientist (Fixed Term) role at University of Cambridge

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

Join to apply for the CG-TIC Computational Biologist/Data Scientist (Fixed Term) role at University of Cambridge

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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.

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.

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 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.

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) 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.

Key Duties Include

• 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.
  
  

What Experience You Will Have

• 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.
  
  

More information about the role is attached in the 'Further Particulars' document.

Informal enquiries regarding this position are strongly encouraged: contact Prof Eoin McKinney ([e-mail]).

Fixed-term: The funds for this post are available for 2 years in the first instance.

This appointment requires a Research Passport application.

We welcome applications from individuals who wish to be considered for part-time working or other flexible working arrangements.

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: 1st June 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
  
  

Apply online

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Part-time

Job function

• Job function

  Research, Analyst, and Information Technology

• Industries

  Research Services

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