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becomes essential. This project will focus on building a comprehensive digital twin of a future quantum computer to investigate how classical subsystems scale and interact, and how this scaling impacts
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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specialist knowledge in mechatronics design and control, and proven programming experience in Python, MATLAB or C/C++. Informal enquiries may be addressed to Professor Liang He (email: liang.he@eng.ox.ac.uk
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(Central Oxford). The post is externally funded and is fixed-term to the 30th September 2026. The integration of electronic and mechanical degrees of freedom in quantum devices, particularly using carbon
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: - solid-state NMR - electron microscopy - lab-based and synchrotron-based x-ray techniques • solid-state electrochemistry, in particular
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plasma channels, and methods for controlling injection of electrons into laser-driven plasma wakefields. This work will be undertaken within the research groups led by Prof. Simon Hooker (Oxford), in
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machine learning, computer vision, human-computer interaction, or similar relevant areas. Experience in research or development on bias, interpretability, and/or privacy in machine learning/AI is necessary
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biochemical reconstitution, electron cryomicroscopy (cryo-EM), advanced bacterial genetics, and phage biology to explore how cells and viruses control the three-dimensional structure of DNA. We investigate how
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electronic health records (EHRs) from multiple UK hospital centres using advanced data analytics including machine learning, deep learning, and statistical techniques—with a particular emphasis on deep