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frameworks to ensure the developed processes are compliant, scalable, and environmentally responsible. Multiobjective optimization algorithms will be employed to balance key performance indicators such as
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(i.e. red agents). However, due to a fragmented market, rapid technical developments, and nascent research the extent of capabilities and optimal solution architectures are not well understood. Current
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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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-electronic and quantum technologies. What you would be doing: Experimental Design and Execution: Plan, conduct and optimize advanced 4D STEM experiments at cryogenic temperatures. This includes working with
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 2 months ago
? This PhD, working with Prof. Marcelle McManus , provides an opportunity to work to explore and advance novel decarbonisation solutions for high-energy use industrial sites. Your project will be co-created
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sensing, and Electromyography (EMG) tools to understand user-device interaction and optimize real-world rehabilitation performance. The student will gain experience in AI, human biomechanics, smart textiles
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modelling tools (CST or HFSS) - Fabricate and test for optimal electromagnetic performance, such as bandwidth, return loss, insertion loss and power-handling. - Develop and characterize new bonding/alignment
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become the bottleneck in achieving optimal performance and trustworthiness. This project will focus on how a federated multi-task learning framework can be effectively designed and optimised to address
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mechanical testing is desirable. In addition, applicants should be highly motivated, able to work independently, as well as in a team and have effective communication skills. Applicants must be eligible
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seek optimal trade-offs between compactness and performance, delivering foundational insights into the future of high-performance electric propulsion systems. Funding 3-year PhD tuition fee (for UK home