[Next-Generation Sequencing Book]
  • [Photo] Eugene McDaid • April 17, 2018

    BACKGROUND

    Pre-clinical – Statistics – RNAseq – DNAseq – Target Discovery – Quantitative Biology – Pharmaceutical

    Paramount have registered an exclusive position with a pharmaceutical company known worldwide. This organisation are keen to appoint an Associate Director or Director level expert in machine learning for their quantitative biology group. This position will work across a number of therapeutic areas, supporting projects in the drug discovery pipeline from target discovery all the way to clinical. You will lead a small team of data scientists with the purpose of providing quantitative insights to biology. You should be passionate about improving the biological understanding of targets and its engagement, and providing image and data analysis solutions to high dimensional datasets.

    This is a fantastic chance to continue your career in an organisation known for their innovative research and progression opportunities. You will be joining a talented and supportive team with expert skills in machine learning and data science.

    RESPONSIBILITIES

    Main Responsibilities:
    • Overseeing a team of data scientists and refining the departmental strategy for using machine learning to transform drug discovery
    • Using machine learning and statistical modelling you will collaborate with drug discovery projects, therapeutic areas and platform teams to identify and deliver solutions for addressing key questions across drug discovery
    • Developing appropriate algorithms, techniques and datasets to answer defined biological questions
    • Establishing academic collaborations to access and drive the forefronts machine learning science

    REQUIREMENTS

    Experience Required:
    • PhD, or equivalent, in mathematics, computer science, statistics, engineering or the life sciences
    • Experience in leading a small team and overseeing project delivery
    • Expertise in one or more of the core machine learning areas such as: ANNs, SVMs, Bayesian approaches, Markov models, Gaussian processes, reinforcement learning, game theory, decision theory, probabilistic rule-based learning.
    • Experience with relevant software tools such as R and Python as well as relevant machine learning frameworks
    • Basic understanding of molecular biology, cell biology, and human physiology
    • Excellent communication skills in English, spoken and in writing

    HOW TO APPLY

    For a confidential discussion about this role or to apply, please contact Jade at jpage[at]pararecruit.com

    Keywords: Machine Learning, Science, Preclinical, Quantitative Biology, RNAseq, DNAseq, Pharmaceutical, Sweden, United Kingdom, Europe

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