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    Opportunity: Senior Rare Disease Analyst / Statistical Geneticist @ Genomics England --London, UK
    Submitted by Eugene McDaid; posted on Thursday, February 13, 2020

    Submitter

    BACKGROUND

    Genomics England have a very interesting and challenging role available for a Senior Rare Disease Analyst, skilled in statistical and human genetics to join their world-leading team.

    To build on the success of the 100,000 Genomes Project, Genomics England are launching a new NHS Genomic Medicine Service. Through 7 Genomic Laboratory Hubs this offers equitable access to the 55 million people in England to the latest genomic medicine and research. This will lead to faster diagnosis and personalised medicine.

    Genomics England applies state of the art approaches to whole genome sequences for processing, analysis, quality assurance and annotation. This includes integrating phenotypic and other clinical data with whole genome sequencing to create a world-leading, high fidelity data repository for the NHS and third party users.

    The Bioinformatics team develops and applies state of the art approaches to whole genome sequences (WGS) in the areas of:
    • Analysis of WGS in cancer and rare diseases 

    • Sequence alignment and variant calling of up to 100 genomes per day
    • Quality assurance and sample provenance monitoring
    This analyst role is part of a highly motivated Bioinformatics team, working as part of a small team responsible for rare disease analysis.

    RESPONSIBILITIES

    Key accountabilities include:
    • Benchmarking tools for quality control, processing and analysis of whole genome sequence data, e.g., alignment, variant callers for variants of different size ranges
    • Performing custom computational analysis for a range of projects in rare disease/germline samples
    • Developing and prototyping new features for rare disease/germline genome analysis in collaboration with internal and potentially external stakeholders
    • Collaborating with software developers responsible for converting prototypes to production pipelines
    • Establishing general bioinformatics resources for day-to-day use by colleagues

    REQUIREMENTS

    Skills required:
    • MSc or PhD with experience of working within Rare Diseases or Bioinformatics/Computational Biology and Systems Biology or equivalent work experience
    • Good knowledge in one or more areas of human DNA analysis, such as rare disease genomics, family based analysis, genetic association testing, risk score prediction, structural variation, pharmacogenomics, typing of complex genomic regions such as HLA/KIR
    • Good knowledge of statistics and/or machine learning, and ideally some quantitative background (e.g. physics, computer science, or maths). These skills could also have been developed, for example, through a PhD in computational biology, statistical genomics, or statistical genetics.
    • Practical knowledge of high throughput sequencing algorithms and available resources. Experience with full cycle of analysing NGS data from sequencing QC to annotation and prioritization of variants.
    • Strong programming skills (Python, R); ability to develop codes as a part of team
    • Excellent technical writing skills
    • A demonstrable ability to cope under pressure and deliver to deadlines
    • Ability to communicate effectively within a multidisciplinary team
    • Flexible and co-operative approach to colleagues
    • Ability to work independently and to show initiative within a team
    • Ability to prioritise and balance competing demands

    COMPENSATION

    There are some great benefits on offer with this role including a competitive salary, pension, generous holidays and more.

    HOW TO APPLY

    Please do not hesitate to contact Harvey Uppal at huppal[at]pararecruit.com or call (+44) 121 616 3407 to discuss this opportunity further.

    Keywords: Rare, Disease, Analyst, Cancer, WGS, WES, Genomics, Bioinformatics, Python, Pipelines, Statistics, Testing, Writing, Variants, Alignment, Statistical, Genetics, NGS, London

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