Research Fellow - Computational Cancer Genomics, University College London, UK

University College London
UCL Genetics Institute; Department of Genetics, Evolution and Environment
United Kingdom London


Applications are invited for a Research Fellow in Computational Cancer Genomics to join the Secrier lab ( on a UKRI Future Leaders Fellowship-funded post in the Department of Genetics, Evolution and Environment. We are seeking an enthusiastic, creative and motivated individual with a keen interest in cancer genomics, clonal evolution and the tumour microenvironment, to explore the mutational processes leading to quiescence and similar cellular states in a variety of cancers. The post holder will be expected to apply various statistical modelling, machine learning and data integration approaches on bulk and single cell genomics and transcriptomics datasets to uncover the mutational and immunological triggers of tumour dormancy. The role will involve the development of new approaches to model and link mutational signatures, clonal evolution and tumour microenvironment interactions in the context of temporary cell states in cancer. Rich multi-omics datasets are available in oesophageal adenocarcinoma, sarcoma and brain cancers from collaborators at the Universities of Cambridge, Southampton, Cologne and the UCL Cancer Institute for this purpose. This position is fully computational, but we will collaborate with our wet lab partners for the purpose of validation of the findings.

The post is funded for 3 years in the first instance. There is the possibility for a further extension of another 3 years as part of the extension of the grant, conditional on satisfactory outputs from the first 3 years.


Applicants must have a PhD in a relevant subject area, e.g. computational biology, bioinformatics, statistics, computer science, mathematics, physics, genetics, biology, biotechnology or similar subject; and extensive programming experience, preferably (but not exclusively) in at least one of the following languages: R, Python, C/C++. Previous experience with NGS data and/or cancer is welcome but not mandatory. The applicants must demonstrate that they have a keen interest in mutational processes, tumour evolution and/or modelling the tumour microenvironment.

Start date

As soon as possible

How to Apply

For a full job description and to apply online for this vacancy please click here:
Informal enquiries should be directed to Maria Secrier on

Closing date for applications: 17th November 2021


Maria Secrier