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Field
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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the growth and stability of individual filaments or organise multiple filaments into various bundled and branched networks. This role will focus on a family of actin-binding proteins that regulates the actin
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immunocytochemistry, electrophysiology and live cells imaging. The aim of the projects is to approximate cellular phenotypes in an in vitro model of Bipolar Disorder (BD), and attributing abnormal network activity
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multiple filaments into various bundled and branched networks. This role will focus on a family of actin-binding proteins that regulates the actin cytoskeleton and links it to other intracellular components
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contact with participants after they have taken part in the research. Support the development and submission of funding bids including: working on data and impact plans, networking with non-academic
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. Through the MRC-funded OpenEP|NET study the post-holder will work closely with the existing study team, supporting system development, technical processing, data management and data science aspects
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, with a special focus on RNA structure and bioinformatics. This position will focus on the development of methods and algorithms for the comparative analysis of metabolic networks. Your future tasks: We
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groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
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About the role The University of Leicester is proud to be part of the UK Nuclear Deterrence Network, a collaborative initiative with King’s College London and the Royal United Services Institute. As