Research Fellow –Cancer Metabolism Data Scientist

Research Fellow – Cancer Metabolism Data Scientist

The Jamal-Hanjani Lab focuses on the biological determinants of cancer metastasis and is a multi-disciplinary group of passionate and determined individuals who will provide the successful candidate with a stimulating and conducive environment to participate and grow as a scientist. The research is conducted across the TRACERx and PEACE consortia, and the CRUK Lung Cancer Centre of Excellence and Francis Crick Institute. These collaborative environments will provide the successful candidate with opportunities to learn from a large network of talented professionals. This project involves working closely with the Karen Vousden lab at the Francis Crick which focuses on how changes in metabolism affect cancer development and progression, the cross talk between tumour and normal cells in the cancer microenvironment and how cancer affects the whole body, including the influence of primary tumours on distant organs and the interplay between cancers and systemic conditions such as obesity, cachexia and aging.

The TRACERx (TRAcking lung Cancer Evolution through therapy (Rx)) study is a UK-wide lung cancer evolution programme which started in 2014 and has to date recruited over 820 patients. It is the first longitudinal cancer genomics study that forms the first national UK consortium focused on deciphering cancer evolution over space and time. TRACERx involves multi-region sequence analyses of lung cancers (5000+ exomes and whole genomes in over 800 patients) from pre-invasive through to primary and metastatic disease setting, in order to understand cancer evolutionary life histories with detailed clinical annotation. The co-primary end points of the study are to investigate the relationship between intratumour heterogeneity and clinical outcomes, and to determine the impact of cancer therapies on intratumour heterogeneity. TRACERx has enabled additional analyses in the areas of immunology, circulating biomarkers, cancer cachexia and body composition, radiomics and tumour microenvironment.

CANCAN Cancer Grand Challenge is an international team of scientists with close collaborations tackling the challenges posed by cancer-associated cachexia, a debilitating wasting syndrome characterised by extensive weight loss. Supported by Cancer Grand Challenges, a global initiative addressing key issues in cancer research, it is funded by CRUK and the NIH. The team focuses on understanding the mechanisms underlying cancer-associated cachexia and developing therapeutic strategies that could reverse it.

We are seeking a collaborative and self-motivated post-doctoral fellow to work on cancer metabolism in a vibrant and highly collegiate environment. The candidate will be expected to develop and make use of bioinformatics techniques to investigate how metabolic dysregulation relates to the development of cancer cachexia and poor outcomes. The project will focus on the analysis of blood mass spectrometry metabolomics data and leverage existing genomic and transcriptomic sequencing data from the TRACERx lung cancer evolution and PEACE research autopsy programmes.

Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Research Assistant Grade 6B, with payment at Grade 7 being backdated to the date of final submission of the PhD thesis. Applications should include a CV and a Cover Letter: In the Cover Letter please provide evidence of the essential and desirable criteria in the Person Specification part of the Job Description. (By including a Cover Letter, you can leave blank the 'Why you have applied for this role' field in the application form, which is limited in the number of characters it will allow.) The role will be available for one year in the first instance with the possibility of extension.

You will hold a PhD (or be close to completion) in a relevant discipline and have a strong track record of independent research, evidenced by high-quality publications and experience analysing complex biological datasets. You will bring expertise in metabolomics data analysis, ideally using mass spectrometry data, alongside experience working with genomic and transcriptomic datasets and applying statistical methods to generate meaningful biological insights.

You will be proficient in computational approaches and programming languages such as R or Python, with the ability to analyse, interpret and communicate complex data effectively to a range of audiences. Experience of collaborating with clinicians and laboratory scientists, mentoring junior researchers, and contributing to multidisciplinary research projects will be highly advantageous.

We are looking for a collaborative, self-motivated researcher with excellent organisational skills, strong attention to detail, and a commitment to delivering high-quality research. You will thrive in a team environment, enjoy working across disciplines, and be confident representing the research group within national and international collaborations.

As well as the exciting opportunities this role presents we also offer some great benefits some of which are below:

• 41 Days holiday (including 27 days annual leave 8 bank holiday and 6 closure days)
• Defined benefit career average revalued earnings pension scheme (CARE)
• Cycle to work scheme and season ticket loan
• On-Site nursery
• On-site gym Enhanced maternity, paternity and adoption pay
• Employee assistance programme
• Staff Support Service Discounted medical insurance

  Our commitment to Equality, Diversity and Inclusion

  As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.