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temperature stability and spatial resolution, to make a leap in this field. The PhD research programme will squarely address these challenges. The PhD candidate should have completed (or about to complete
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How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded for home students or EU students with settled status; the successful candidate will receive a tax-free stipend set at
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, mathematics, engineering, computer science, or related subject) Proficiency in English (both oral and written). Knowledge in cryptography is desirable. Studentship and eligibility This studentship is suitable
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boundaries. This fully funded PhD scholarship is suitable for students with a background in Engineering Design, Smart Manufacturing, Aerospace Engineering, Mechanics, Computer Science, Mathematics, Life Cycle
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considered. Qualifications/Skills PhD degree in a programme relevant to human-computer interaction and/or critical computing, ideally in Computer Science, Industrial Engineering, Interaction Design, or a
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select 'Mechanical and Manufacturing Engineering' under ‘Programme’. Please quote the advertised reference number, ‘FP-CTS-2025’, under the ‘Finance’ section of your application. Please note that 1 January
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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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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PhD Project: Advanced 3D/4D-Printing of Responsive Biomaterial Devices Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre
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PhD Project: 3D-Printed Drug Delivery “Microbots” for Personalised Healthcare Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing