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demonstrating coherent spin shuttling, shuttling-compatible high-fidelity qubit control and further ingredients for a shuttling-based architecture, using devices from academic or industrial fabrication. Key
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advanced computing applications. The selected candidate will contribute to the design, prototyping, and testing of photonic devices and circuits aimed at enabling next-generation computing architectures
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fundamental research in physics-informed and symmetry-aware machine learning for nonadiabatic excited-state molecular dynamics. Develop and evaluate equivariant graph neural networks and related architectures
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implementing CRISPR-based genetic and pharmacologic screening approaches. Exploring enhancer biology and three-dimensional genome architecture through advanced genomic technologies. Conducting molecular analyses
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We are seeking a full-time Postdoctoral Research Assistant in Machine Learning to join Torr Vision Group at the Department of Engineering Science (central Oxford). The post is fixed-term for 1 year
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technologies, including drones, robotics, and self-driven laboratories. The appointees will engage in research on the development of intelligent hybrid power architectures to support autonomous operation in
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to corporate, investment and industrial partners. It is at the forefront of training in nanotechnology, and has a strong media presence aimed at educating the public and bringing transparency to this emerging
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be finalised by July 2026. Supported Areas for START Engineering Energy Resilience: Power electronic converters for distributed energy resources and microgrids; High voltage DC transmission and
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be finalised by July 2026. Supported Areas for START Infocomm Technology Information Security: Mobile security, cyber-physical systems, IoT security, security analytics, operational cybersecurity
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at https://www.jmu.edu/cise/engineering/index.shtml. Conditions of Employment: Employment is contingent upon the successful completion of a criminal background check. E-Verify Notice: After accepting