598 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"BioData" Fellowship positions in United Kingdom
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the School of Politics and International Studies at Leeds. The overall objectives of this project are to contribute to global climate change research and practice by exploring 1) the distinctive political
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offloading strategy via simulations and live demonstrations. Job Requirements A Ph.D degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical
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approaches, you will investigate how gene expression variability drives drug-tolerant subpopulations. This role sits at the intersection of molecular genetics, chemical biology and data science, with strong
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of study. The successful applicant will have an extensive knowledge of dynamical systems, computational neuroscience and data science. In addition, we expect the candidate to have: Experience of interdisciplinary
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estimation technologies (AET) from facial images. This is an exciting opportunity to contribute to cutting-edge biometric research at the intersection of computer science and digital identity technologies
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01/03/2026 – 31/01/2028 Job-share may be considered. About you The successful candidate will have a PhD degree or be near to completion in a social science. If the degree has not yet been granted
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environmentally sound management of the materials contained in lithium-ion batteries. Researchers at the University of Birmingham will be investigating separation technology efficiency and characterisation
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and Infection, and the School of Infection, Inflammation and Immunology of the University of Birmingham. Person Specification Undergraduate degree in biological or biomedical sciences, and a PhD degree
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at Leeds and Reading are also members of the National Centre for Atmospheric Science (NCAS). The successful candidate will be fully integrated into this consortium, as well as becoming a member of the UKESM
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Gravitational-Wave Astronomy Using Artificial Intelligence, to work on computational Bayesian inference methods and their astrophysical applications. Southampton's School of Mathematical Sciences is home to a