575 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" Fellowship positions in United Kingdom
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to publish in nation-al/international journals (commensurate with stage of career). Be experienced in the computational analysis of multivariate chromato-graphic and mass spectrometric datasets. To be
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at the local, national and international levels. We are a diverse team of researchers, technology specialists and security experts focused on delivering tangible solutions for law enforcement and other security
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of Applied Health Sciences and will play a central role in delivering the NIHR Research Professorship awarded to Professor Joht Singh Chandan: (NIHR306365, https://fundingawards.nihr.ac.uk/award/NIHR306365
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well as a PhD (or equivalent level 8 qualification) in AI, Data Science, Computer Science, Biomedical Engineering, or related field, or equivalent experience. Please view the job description and person
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are expected to contribute to class teaching on the undergraduate degree programme and other teaching on the undergraduate or postgraduate programme as may be available. While our class teaching needs can arise
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As a University of Applied Learning, Singapore Institute of Technology (SIT) works closely with industry partners to develop applied research capabilities that translate directly into real-world
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School of Physics and Astronomy. You will carry out a research programme analysing stellar populations and chemical enrichment processes in galaxies using large galaxy surveys such as SDSS and DESI, as
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expertise in soil, plant and microbial systems across scales, with the Cranfield Environment Centre , which has expertise in environmental informatics and modelling and is the UK National Reference Centre for
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Job reference: BMH-031095 Salary: £59,966 - £67,468 per annum depending on experience Faculty/Organisational Unit: Biology, Medicine Health Location: Oxford Road Employment type: Fixed Term Division
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working with Johnson Matthey, but aligned with the EPSRC funded Programme Grant “Dialling up performance for on demand manufacturing” (EPSRC reference: EP/W017032/1). Our vision is to create a toolkit and