367 computing-"https:"-"https:"-"https:"-"U.S" Fellowship positions in United Kingdom
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- Xi'an Jiaotong - Liverpool University
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experience in Mechanical Engineering, Applied Mathematics, Physics, Acoustics, Computational Science or a closely related discipline. Strong experience in numerical/computational modelling (e.g., FEM
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Future Leaders Fellowship programme at the School of Physics and Astronomy, University of Birmingham. The position is available for up to three years (until May 2029). The project focuses on nanoscale
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diverse team of faculty members, engineers, and industry partners, including renowned researchers at the College of Computing and Data Science (CCDS) at NTU. Technical skills, natural curiosity, versatility
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Job Title: Research Fellow (Data Scientist) - INNOVATE+ Project Department/School: School of Computing, Engineering and Intelligent Systems Campus: Derry~Londonderry campus Salary: Grade 8 (£48,822
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postdoctoral scientist to work on our Blood Cancer UK-funded programme developing next-generation, off-the-shelf immunotherapies for acute myeloid leukaemia (AML). This three-year project will harness cytotoxic
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on the National Institute for Health Research (NIHR) RESPOND Programme. This was a 5-year project to develop and trial methods for improving responses to deteriorating postoperative patients. The post will
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biology, mathematical and computational finance, numerical analysis, machine learning and data science or the Oxford Centre for Industrial and Applied Mathematics (OCIAM). The successful candidates will be
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detector approximately eight times larger than that used in T2K. Hyper-Kamiokande will undertake a rich programme of physics, including studies of CP-violation, neutrino oscillations, proton decay
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Robert Gordon University (RGU). METASIS is a collaborative research programme advancing next-generation solid oxide steam electrolyser (SOSE) technology for clean hydrogen production. Led by Robert Gordon
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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