Data Scientist

This is a unique opportunity for an Data Scientist to contribute to an innovative and multidisciplinary project, which focuses on developing a novel breath test for the early detection of gastrointestinal cancers (oesophageal, gastric, liver, pancreatic and colorectal).

This position is funded by NIHR as part of the PANACEA (PAN Alimentary Cancer Exhaled breath Analysis) programme, led by Professor George Hanna. You will join a collaborative and dynamic team, working closely with internal and external colleagues, including leading scientists from Imperial College and partner institutions.

In this role, you will be responsible for driving key aspects of the PANACEA research programme, specifically:

Manage the day-to-day running of volatile organic compound analytical laboratory with a focus on the breath analysis workflow. Untargeted/chemometric data analysis of large mass spectrometry datasets; Develop predictive models and data analysis pathways; Ensure models and pathways generated are compliant with relevant international standards; Support the development of quality control pathways to increase quality and productivity. Work closely with PANACEA co-applicants and collaborators, and other members of the laboratory.

You are expected to hold A-levels/Degree in relevant scientific subjects or equivalent vocational qualifications, plus work experience, preferably in a relevant technical/scientific role or the equivalent work experience in a relevant technical or scientific role. It is also expected for you to be familiar with chemometric analysis of large datasets in languages such as Python or R.

The chance to work with a leading research group led by Professor George Hanna, a world-leading expert in breath analysis.Exceptional opportunity to work within a highly collaborative and supportive environment and contribute to high-impact research in the field of cancer diagnostics.Enhance your career and personal development and the opportunity to continue your career at a world-leading institution