406 data-"https:"-"https:"-"https:"-"https:"-"INESC-TEC" Fellowship positions in United Kingdom
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of £37,897 to £45,580 per annum, with potential progression up to £52,067 per annum Apply by: 10/05/2026 Role Description We welcome applications from enthusiastic bioinformaticians or data scientists to join
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directly from experimental and process data, these models will enable a shift from iterative, trial-and-error fabrication towards predictive and data-driven manufacturing. We are seeking a highly motivated
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professional services teams. Further information For further information please contact Prof. Catriona McKenzie, e-mail c.mckenzie@exeter.ac.uk . Applications should be made via our website. For more information
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). Demonstrable familiarity with technology translation,commercialisation of research, or similar entrepreneurial activity. Experience in method development, validation, and quantitative data analysis. Experience
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genetic, neuroimaging and clinical data, will be combined to generate novel insights into biological and developmental processes contributing to autism and related traits. You will be responsible
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mean temperatures were approximately 5-10°C warmer than the 1970-2010 average. The role will involve the generation of ecophysiological data as measurements of plant performance and generating
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, there is potential for involvement in data analysis leading to conference presentations and/or authorship in peer-reviewed journals. Education & Leadership: You will be encouraged to deliver formal
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to £45,580 per annum, with potential progression up to £52,067 per annum We welcome applications from enthusiastic bioinformaticians or data scientists to join our flag-ship project ‘Developing a resilient and
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Responsibilities: Develop chemical and biochemical assays and analyses, conduct comprehensive laboratory experiments, data analysis and reporting. Design, develop, and test microfluidic devices for miniaturised
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information/data from one structure can be used to manage similar structures from the same population. New machine learning, sensing and digital twin technologies will be developed with the aim of driving new