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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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-skills. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How to apply You must apply
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Motivation: Soft and flexible materials (e.g. polymers, hydrogels) have revolutionised many areas of science and technology ranging from flexible electronics to soft robotics. Scientists now predict
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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
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in a related discipline. This project would suit motivated graduates from a wide range of STEM backgrounds—including environmental, civil, chemical or mechanical engineering, computer science, robotics
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, with minimal computational cost. By developing an advanced reduced order modelling framework, this project will empower engineers and designers to achieve more with less—delivering high-impact decisions
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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed