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will aim to make foundational work in glass-based RF components and packaging techniques, with specific aims including: - Investigate design methods that are suitable multi-port RF components using 3D EM
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will be around 6th Oct 2025 Project Overview An enthusiastic researcher is invited to join a team to work on the EPSRC Industrial Doctoral Landscape Award project in collaboration with industrial
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conceptual and experimental framework for engineering functional nanostructures from bottom-up principles. The work will benefit from access to robotic processing platforms and state-of-the-art microscopy and
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qualitative and quantitative methodologies, and executed by an international team of sociologists and political scientists. The doctoral students based at Queen Mary University of London will work across three
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paper production, benefiting both industry and the environment. Most of the work will be performed within the School of Applied Sciences, University of Huddersfield, however, this is an industrially
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sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
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Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring
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, drugs, antibodies, human lymph system, seconds, days, years). This project is in collaboration with GSK and we will work closely with experts from GSK. The Departments of Mathematics is part of
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
both academic and professional sports performance environments, gaining unique insights and opportunities to translate cutting-edge science into practice. The candidate will work closely with the team
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sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The outputs of this work will support practitioners in making informed investment decisions