306 Computer-Science-"https:"-"https:"-"Data-driven-Materials-Modeling" PhD positions in United Kingdom
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only of storing information, but also of manipulating, organising, and retrieving it through molecular data structures analogous to those used in computer science. Building on our pioneering experimental
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your programme of study: search for the ‘Course Title’ using the programme code: “8100F” select ‘PhD Chemistry (full time) - Chemistry' as the programme of study You will then need to provide
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Associate and Assistant: A recognised first class masters degree (or equivalent) in Aerospace, Mechanical Engineering or a closely related discipline In addition: Experience in computational mechanics
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
qualification equivalent to a Master’s degree in Chemistry, Mathematics or Computer Science by the start of the PhD; A curious mind-set and strong background in quantum crystallography and its underlying
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The continuous release of Earth Observation (satellite) data and the emergence of Machine Learning methods open up new possibilities for understanding forests. These large datasets provide complementary information on 3D structure (GEDI lidar, BIOMASS P-band radar, NISAR L-band radar) and high...
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offer visa sponsorship for this role. Candidate requirements The successful candidate should have a good honours degree or a master’s degree in computer science, mathematics, civil engineering, mechanical
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are excited to work across disciplines and contribute to cutting-edge research at the interface of biology, chemistry, imaging, computation, and AI. Molecular Perturbations: Chemistry Engineering Biology
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Phd Studentship in Computer Science: Empirical Security Assessment of AI Decision Engines in Cyber-Physical Systems Award Summary 100% home fees covered, and a minimum tax-free annual living
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sites, highly engineered geological repositories or in the marine environment. However, redox controls on porewater chemistry in these environments is poorly understood and requires robust datasets
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(DoSChem) – Austria’s largest doctoral training program in chemistry. DoSChem brings together more than 200 doctoral students and over 50 PIs, fostering interdisciplinary and curiosity-driven research