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to lead the design and delivery of high-quality learning that underpins our regulatory, quality assurance and student lifecycle activity. This is a chance to make a real institutional impact at a time
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to
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the relevant information for the clearance process. Please see the security vetting link from UK Government on requirements. https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance
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Ability to lead and work in teams Essential Application/Interview Experience and capability in blast computational simulations using codes such as Viper:: Blast, machine learning, and/or LS Dyna Desirable
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design and implementation of visual cues detection on video datasets (face and gesture), context-aware multimodal analysis, machine learning/self-supervised learning for automatically detecting subtle
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attacks or data leaks. This is particularly concerning given how widespread and security-critical these devices are: they are used for controlling vital computer systems in many domains, such as critical
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agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.05.2030 Reference no.: 5502 Explore and teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous
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opportunities. To learn more follow the link to our benefits website . The University of Leeds has engaged the services of Berwick Partners (part of the Odgers group), to whom applications should be sent
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Department Marketing, Student Recruitment and Admissions (MSRA) You can find more information about the department on our website: https://www.essex.ac.uk/information/professional-services Duties
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refer to the Candidate Information Pack. For further information, please see the choir website: https://www.jesus.cam.ac.uk/chapel-and-choir . For an informal discussion about the post, please email