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analytical methods for the analysis of linked data from electronic health records and genomic or molecular sources. Strong statistical skills (e.g. proficiency in R or Stata), along with excellent writing
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sensors and monitoring technologies with data fusion and AI analytics, this research will enable timely identification of deterioration processes and assessment of their evolution/extent.Position 3
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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on advancing research in customer analytics. The role holder will work with the Cambridge Service
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presentation of results of collaborative research projects. Most of your analytical work will be based on Real World Data (RWD), in many cases from datasets mapped to the OMOP common data model such as the
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project (e.g. a PhD or MA thesis) Strong analytical skills (as evidenced in research projects and/or methodological training) Strong writing skills (as evidenced in a short writing sample) Desirable
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project (e.g. a PhD or MA thesis) Strong analytical skills (as evidenced in research projects and/or methodological training) Strong writing skills (as evidenced in a short writing sample) Desirable
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staff. Attending project steering group meetings. Essential Criteria A degree (or equivalent) in engineering, microbiology, physics, or a related field. Strong analytical skills and experience with data
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outlined below. Develop research objectives and proposals for own or joint research, with assistance of a mentor if required Contribute to writing bids for research funding Analyse and interpret data Apply
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. Ability to work independently as well as part of a research team. High level analytical capability and an inquisitive mind. Ability to communicate complex information clearly A willingness to travel to
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sciences field. Experience performing high-quality bioinformatics, genomics or computational biology analyses. High level analytical capability Ability to communicate complex information clearly Fluency in