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(or equivalent) in Physics, Mathematics, Mechanical or Aerospace Engineering, Computer Science or a related discipline. You should be highly motivated, and would be able to work independently as
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for wastewater treatment, do analysis of both sludge and water by using various analytical instruments, and conduct bioinformatic analysis. Candidates with high motivation and degrees in environmental engineering
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applications such as drug delivery. Possible outcomes and goals: Studying the interaction of collections of synthetic cells (i.e. proto-tissues) for tissue engineering and regenerative medicine applications
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Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration Research Centre (AIRC
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engineering, digital technologies, and systems thinking. The university’s strong reputation for applied research and its focus on technological innovation ensure that this project will be well-supported, with
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horizons. It plays a pivotal role in the £65 million Digital Aviation Research and Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent
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physiology etc. This PhD project is suitable for applicants with a background in Electrical and Electronic Engineering or closely related fields. Candidates with a strong interest in RF engineering and/or
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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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science, engineering, mathematics, or related subject) Proficiency in English (both oral and written) Essential to have strong foundations in computer systems through degree courses or equivalent work experience
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of the GDPR, Federated Learning (FL) has emerged as a leading privacy-preserving technology in Machine Learning. Despite its advancements, FL systems are not immune to privacy breaches due to the inherent