[Next-Generation Sequencing Book]
  • [Photo] Eugene McDaid • November 27, 2018

    BACKGROUND

    One of the world's most prestigious pharmaceutical companies is expanding their drug discovery research facility in Oxford and seeking a talented Bioinformatics, Data Scientists, Machine Learning Enthusiasts, Statistical Geneticists and Computational Scientists. This is a hands-on position, where you will be working with large data repositories, using cutting edge data science techniques and Bioinformatics analysis to gain a deeper biological understanding of disease and discover novel targets.

    RESPONSIBILITIES

    • Routinely analysing a wide variety of data-sets, including genomic, transcriptomic, proteomic, stem cell and CRISP-R
    • Using advanced machine learning to discover novel targets, and accelerate the drug discovery process, from early pipeline towards proof of principle in animal models
    • Work collaboratively across all departments

    REQUIREMENTS

    • PhD in Computational Biology, Bioinformatics, Mathematics, Physics, Machine Learning, Statistical Genetics, Systems Biology or a related discipline
    • A minimum of 2 years' Post-doctoral or industry relevant experience
    • A passion for advanced analytics, with a background in one or several of the following: machine learning, deep learning, artificial intelligence, algorithm development
    • Experience of applying AI/Machine learning methods for drug discovery/target identification

    HOW TO APPLY

    This is a fantastic opportunity to work with one of the world's leading pharmaceutical companies, work with cutting edge technologies and help get more efficient treatments to patients faster than ever before. On offer is a competitive benefits package, brilliant location with excellent transport links, academic freedom to publish and stimulating projects. To find out more about the opportunities available, send your CV to Emilie Francis (efrancis[at]pararecruit.com) or give Emilie a call on 0121 616 3477.

    Key words:
    Drug discovery, Systems Biology, Bioinformatics, Data Science, Machine Learning, Algorithm design, Drug targets, Post-Doc, Oxford, Pharmaceuticals, Artificial intelligence, Statistical genetics, Genomics

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