Research Training Fellow in Cancer Data Science and Epidemiology

THE INSTITUTE OF CANCER RESEARCH
London, Sutton, London, United Kingdom
Yesterday
£47 – £52 pa

Salary

£47 – £52 pa

Job Type
Contract
Work Pattern
Full-time
Posted
23 Sep 2026 (Yesterday)

Key Information

Salary: Research Training Fellow 1-2 Salary Range: £47,175 - £52,396 per annum. Commencement on the salary range is subject to comparable skills and experience.Appointment is expected at Research Training Fellow 2 level (Senior Research Fellow) although outstanding candidates with less experience may be appointed at Research Training Fellow 1 level (post-doctoral)

Reporting to:Professor Montse Garcia-Closas

Duration of Contract: Fixed Term for 2 years in the first instance, with a view to extension subject to funding.

Hours per week: 35 hours per week (Full Time)

Location:Sutton

This role is eligible for ICR Sponsorship. If this is your first visa in the UK, support will be provided for costs associated with Visa application. If you are considering relocating to the UK, further information can be found here.

Job Details

Under the guidance of Professor Montse Garcia-Closas, Group Leader Integrative Cancer Epidemiology, Division of Genetics & Epidemiology, we are seeking to recruit an experienced, motivated quantitativeResearch Training Fellow to lead data integrative analyses in large-scale epidemiological studies of cancer and apply innovative methods in epidemiology, statistics and data science to multimodal cancer research. The successful candidate will play a key role in the team research focusing on integrating diverse data modalities using advanced statistical and AI methods, including emerging life-sciences foundation models, to investigate cancer aetiology, identify biological and clinical subtypes, and develop robust models of cancer risk that can inform prevention, screening and early detection. This is an excellent opportunity for candidates interested in using innovative data-driven approaches, working closely with epidemiologists, data scientists, biostatisticians, and data engineers, contributing to high-impact research on cancer prevention and risk.

About you

The successful candidate will work in a collaborative and internationally connected research environment, with opportunities to lead analyses, develop new expertise and contribute to high-impact scientific publications, andmust have:

  • A PhD, or equivalent research experience, in computer sciences, epidemiology, biostatistics, machine learning or a closely related quantitative discipline.
  • Strong knowledge of analytical methods relevant to epidemiological and biomedical research, including machine-learning methods for high-dimensional or multimodal data.
  • Good understanding of epidemiological study design, bias and interpretation.
  • Theessentialskills as detailed in the person specification on the job description.

Department/Directorate Information

The Integrative Epidemiology Team at The Institute of Cancer Research led by Professor Garcia-Closas is located at the ICR Sutton Campus. The team forms part of the Cancer Epidemiology and Prevention Research Unit (CEPRU), a joint initiative between the ICR and Imperial College London focused on advancing cancer epidemiology through interdisciplinary research and training.

The team uses large-scale population data to investigate the causes of cancer, understand carcinogenic processes, and improve risk prediction for precision prevention. A central resource for the team is the Breast Cancer Now Generations Study, a national cohort of over 110,000 women in the UK followed since 2004.

Research in the team combines epidemiology and biostatistics with emerging approaches in data science, including analyses of mammography and pathology images and integration of multi-modal data.

What we offer

  • A dynamic and supportive research environment
  • Access to state-of-the-art facilities and professional development opportunities
  • Collaboration with leading researchers in the field
  • Competitive salary and pension

We encourage all applicants to access the job pack attached for more detailed information regarding this role.

For an informal discussion regarding the role, please contact Professor Montse Garcia-Closas via

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