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    Clinical Research Scientist - United Kingdom - Thrombosis Research Institute

    Thrombosis Research Institute
    Thrombosis Research Institute United Kingdom

    1 week ago

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    Description

    The Thrombosis Research Institute is a renowned institution dedicated to advancing research in the field of thrombosis and cardiovascular health outcomes. The institute has been involved in laboratory studies, randomised clinical trials and large international observational registries. The institute is now moving into the area of large national and regional databases, as well as studies using administrative claims, laboratory results, EHR data, as well as large-scale biomedical databases like UK Biobank. For further information on the scope of our research, please visit:

    The Thrombosis Research Institute is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, or any other characteristic protected by law. We encourage candidates from all backgrounds to apply.

    Role Overview:

    You will lead the TRI statistical genomics and evolutionary genetics research. You must have expertise in current statistical genetic and population genetic methodologies. You must have experience accessing, processing, and integrating large publicly available genetics and population genetics databases and must be facile in working on a variety of data storage and analytic platforms. You will contribute to the overall success of our organisation by applying data mining techniques and statistical modelling to population health data to better understand relationships between genetics and genomics factors and other patient characteristics and outcomes. Through analysing genetic/genomic factors, lab samples, wearable device output, EHR, registry, and organisational data, you will contribute to identifying new models for evaluating and predicting outcomes, answering important questions about connections between genetic profiles and key clinical outcomes, as well as new methods in the prediction of these outcomes. The analytic findings will help healthcare providers understand and identify methods to improve population heath. This work contributes to the development of new strategies and tactics to improve overall healthcare delivery.

    You will develop new methods for approaching these complex statistical problems. Where appropriate and possible, you will collaborate with researchers in other universities and laboratories to move the clinical and genetic statistics field forward in meaningful ways. You will ensure TRI studies are planned and implemented to the highest standards, in compliance with ICH-GCP guidelines, TRI standard operating procedures (SOPs) and all applicable regulatory guidelines.

    Key Responsibilities:

    • Work with large sets of genetic, proteomic and device output data to identify connections with patient clinical outcomes
    • Apply appropriate data analytic techniques and statistical modelling to large amounts of population health data to discover optimal treatment and utilisation patterns that can lead to improved health and financial outcomes
    • Monitor trend of cost, utilisation and quality of care for a defined patient population, identify factors driving the changes and predict future trend
    • Support acquisition and implementation of new information sources, data collection strategies, data governance and analytics
    • Work with product team to develop new analytic and reporting methods.
    • Help staff with data manipulation and analytic methods to improve analytic deliverables when required
    • Handle and secure highly confidential and sensitive analyses and documentation
    • Learn IT tools and analytical methods appropriate for projects
    • Collaborate closely with clinical investigators, other statisticians and statistical programmers to share and document this knowledge
    • Participate in all statistical aspects of a project, with minimal guidance
    • Collaborate with project leader, principal investigator, other clinical investigators, and external government or industry representatives to affect significant decisions regarding the project, and to jointly achieve objectives and timelines. Contributes constructively to project discussions.
    • Understand the contracted scope of work and estimates hours and resources expected to complete each project.
    • Proactively identifies potential out-of-scope activity
    • Create timelines for statistical project management with minimal or no assistance
    • Adhere to SOPs of the functional department as they apply to documentation and validation of clinical research statistics
    • Understand and remain abreast of guidelines from regulatory agency as they apply to statistics and programming
    • Demonstrate a solid understanding of the clinical drug and/or device development process
    • Collaborate effectively with a variety of types of individuals: programmers, statisticians (both junior and senior), medical personnel, and representatives within the business community
    • Develop leadership and communication skills and share them with others.
    • Learn about clinical aspects of the research, as appropriate
    • Perform other related duties incidental to the work or as assigned

    Desired Skills and Experience:

    • A PhD in a Statistics, Biology (computational), or Data Science related field
    • Experience applying data mining techniques and statistical modelling in healthcare industry settings, with SQL, Python or R as tools
    • Experience using clusters or cloud computing such as Google Cloud, AWS, Azure
    • Experience analysing genomics, epigenetics, transcriptomic and other -omic data, including pre-processing, alignment, quality control, variant calling and liftover
    • Preferred understanding of health data formats including: EMR, lab and pharmacy
    • Experience applying and interpreting machine-learning/statistical methods for phenotypic and omics data
    • Excellent oral and written communication skills; ability to present complex information in an understandable and compelling manner
    • Excellent critical thinking and problem-solving skills
    • Strong interpersonal, communication and collaboration skills
    • Ability to present concepts and analysis in front of diverse audiences
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