Bioinformatics Data Scientist

  • Location

    Cambridge, Cambridgeshire

  • Sector:

    Life Sciences

  • Job type:


  • Salary:


  • Contact:

    Janne Bate

  • Contact email:

  • Job ref:


  • Published:

    1 jaar geleden

  • Expiry date:


  • Startdate:


Our client in drug discovery and development are seeking a Bioinformatics Data Scientist to join their bioinformatics team working with multi-disciplinary project teams throughout the discovery, pre-clinical and clinical pipeline, with a focus on NGS technologies, multi-omics data, functional genomics and structural bioinformatics, to drive new target evaluation, pre-clinical and clinical research.
This role will provide the candidate with an opportunity to apply their computational and mathematical skills to develop innovative methods for analysing complex multi-layered omics data to identify novel targets and biomarkers associated with diseases.

The ideal candidate will have experience in data science research in data mining, statistics, mathematical modelling and machine learning.
* Providing support to the bioinformatics team in applying innovative statistical methods & data integration
* Leading the development of analytical models using statistical, mathematical and machine learning
* Developing and implementing novel statistical approaches to analyse diverse multi-layered omics data types (eg. genomics, transcriptomics, proteomics) to identify novel drug targets, biomarkers and therapeutic mechanisms methods for biomarker development and patient stratification strategies
* Integration and meta-analysis of public & internal data sets to generate testable hypotheses approaches
* Staying up-to-date with novel bioinformatics methodologies, tools and applications
* Maintaining and expanding the team's knowledge of high-throughput "omics" data sources
* Contributing to the general development of Astex's bioinformatics platform and capabilities

* Programming proficiency with Python, R or similar
* Degree
* Demonstrated working knowledge of statistical methods and graphical models
* Knowledge of machine learning methods
* Experience in developing algorithms and workflows
* Good understanding of NGS techniques, cancer genomics and analytical approaches for analysing multiomics and multimodal data sets