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at Durham, working in hardware and embedded security, confidential computing, trusted execution, secure AI, and related areas. This post is suitable for candidates with a wide range backgrounds relevant
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at Durham, working in hardware and embedded security, confidential computing, trusted execution, secure AI, and related areas. This post is suitable for candidates with a wide range backgrounds relevant
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leave, plus 9 buildings closed days for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by
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thrusts within the lab’s multi-agent security programme. You should possess a completed PhD/DPhil (or thesis submitted by the start date) in Computer Science, Machine Learning, AI, Security, Robotics
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operando data related to battery degradation and safety. You will develop and implement advanced deep learning models to analyse multi-modal operando data from accelerated stress testing, with the aim
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Holiday Entitlement: 33 days annual leave, plus 9 buildings closed days for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the
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evaluating computational methods, analysing imaging data, collaborating with clinicians for real-world impact, and contributing to publications. About You PhD (or near completion) in computer
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thrusts within the lab’s multi-agent security programme. You should possess a completed PhD/DPhil (or thesis submitted by the start date) in Computer Science, Machine Learning, AI, Security, Robotics
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hardware and embedded security, confidential computing, trusted execution, secure AI, and related areas. This post is suitable for candidates with a wide range backgrounds relevant to cyber security
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intelligence shapes welfare governance and migration management across Europe. The role is jointly based in the School of Society and the Environment and the School of Electronic Engineering and Computer