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, economic viability, and robustness to realistic operational uncertainty. PhD (or equivalent) in control engineering or closely related discipline. Track record in at least two areas: model predictive control
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, which is not possible with current systems. It aligns with key STEM themes and EPSRC’s strategic focus on ‘Engineering’, ‘Health and Medical Technologies’, and ‘AI, Digital, and Smart Applications
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PhD Project: 3D-printing next-generation electro-actuators for soft robots and devices Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive
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applicants embarking on a brand-new LSBU research programme—current PhD students and LSBU staff members are not eligible for this award. Why choose LSBU for your doctoral journey? LSBU is a dynamic, applied
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
on integrated GRMs. The successful candidate will hold a PhD (or be close to obtaining) in Applied Physics, Material Science, Nanotechnology, Chemistry or Electrical Engineering with experience in photonics
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at https://www.aalto.fi/en/study-options/aalto-doctoral-programme-in-electrical-engineering . WE OFFER The position will be filled for a period of 4 years (2 + 2). The starting date is in October 2025 or as
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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, engineering (e.g.: mechanical, electrical, electronic, materials) or a related subject. A relevant master’s degree and/or experience in the use of wearable technology will be an advantage but not essential
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing