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Field
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staff and the adults with learning disabilities that they support. The post requires experience of conducting recruitment and data collection in large studies and previous experience of working with
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will increase to Grade 6. Desirable criteria Experience with skeletal muscle tissue and single muscle cell (myofiber) handling Experience in handling, processing, analysing and interpreting large data
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate
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include undertaking research, as appropriate, to support the project including contributing to the delivery and analysis of a large-scale questionnaire survey, conducting qualitative research interviews
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criteria Experience with skeletal muscle tissue and single muscle cell (myofiber) handling Experience in handling, processing, analysing and interpreting large data sets Experience in mentoring, leading and
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, handling and processing of large data sets, knowledge of data acquisition systems, signal and image processing as well as experience in measuring acoustic pressures in cavitating liquids and high-speed
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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To undertake research on the evolution of prokaryotic pangenomes using machine learning and AI approaches. The work will involve the analysis of large prokaryotic genome datasets, the development
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candidate must have experience in the following areas: molecular cell biology, plant phenotyping, and image/data analysis, as well as working as part of a large team. A track record of publishing research is