[Next-Generation Sequencing Book]
  • [Photo] Eugene McDaid • August 8, 2018

    BACKGROUND

    One of the world's most prestigious pharmaceutical companies is expanding their drug discovery research facility in Oxford and seeking a Senior Data Scientist to develop and lead a growing Computational/Data Scientist team. In this position, you will be working on experimental, early phase discovery projects, which demands a passionate, highly creative and mathematical mind.

    RESPONSIBILITIES

    Senior Data Scientist responsibilities would be:
    • Use cutting-edge technologies such as single cell sequencing and CRISPR genome editing.
    • Use experimental training data to predict which targets need to experimentally tested.
    • Interact across departments with internal stakeholders from Bioinformatics, Discovery Biology, Pharmacology, etc.
    • Strengthen external collaborations with academic community.

    REQUIREMENTS

    Requirements of the position:
    • PhD or Post-Doc in Computational Biology, Mathematics, Physics, Machine Learning, Statistical Genomics or a related discipline
    • Advanced statistical ability, proficient developing machine learning techniques or statistical modeling
    • Experience working with RNA-seq, Single cell sequencing data or functional genomics
    • Leadership skills
    • Ability to meet deadlines and work in a fast-paced environment

    COMPENSATION

    This is a fantastic opportunity with a leading global pharmaceutical company that offers a flexible and collaborative work environment, where publishing is actively encouraged. Employees have access to cutting edge technology and have the freedom for creative intellectual independence.

    HOW TO APPLY

    For more information on this opportunity, send your CV to Emilie Francis at efrancis[at]pararecruit.com. For an informal chat, call Emilie on 0121 616 3477.

    Key words: Data Science, Computational Biology, Data Modelling, Drug Discovery, Genomics, Data Modeller, Computer Science, Oxford, London, Cambridge, Pharmaceuticals, Machine Learning, Artificial Intelligence, Systems Biology

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