12 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"Shenzhen-Technology-University" PhD positions at University of Surrey
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Quantum materials underpin key emerging technologies in quantum computation, sensing, and low-energy electronics (e.g. topological insulators, topological superconductors, spin liquids, superfluid
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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This studentship is fully-funded by an EPSRC Industrial Doctoral Landscape Award in partnership with AWE plc. The successful applicant will be welcomed into our world-leading research programme
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scintillators to X-rays and gamma rays using radioisotopes and X-ray generators. The student will be registered on the Physics PhD program; however, the nature of this research project is highly multi
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the average values of the widths and spacings between two adjacent resonances. This energy range is called the “unresolved resonance region” (URR). Current computational methods treat the resonances in the URR
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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-leading research programme investigating key nuclear reactions for both fundamental physics and applications. The aim of the project is to establish new methods to measure properties of Auger electron
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PhD Studentship: Robust quantum control for quantum error correction The development of fault-tolerant quantum computing is one of the most coveted aims of quantum technology. It will bring about a
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Environment This studentship is based at the Centre for Vision, Speech and Signal Processing (CVSSP). CVSSP is: The largest UK research centre in its field Ranked 1st in the UK for Computer Vision research
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integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative