39 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Edinburgh Napier University" PhD scholarships at University of Nottingham
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data-driven methods to develop an inverse design framework for manufacturing systems. Together, we will advance the capability to design manufacturing systems that embed reliability, resilience
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for candidates who can demonstrate strong research potential. Suitable backgrounds include, but are not limited to: Human Factors Law (particularly law and technology, medical law, or data governance) Psychology
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global manufacturers. For details, visit the MTC website . For further information on this PhD position please contact Dr Sara Wang (Sara.Wang@nottingham.ac.uk ) Closing Date: 27th February 2026. Proposed
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without having contacted our team first Please contact Dr Abdelkhalick Mohammad for further information Due to the high volume of applications we will only be contacting shortlisted candidates. Applications
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MEng degree in Electrical and Electronics Engineering or Aerospace Engineering. To apply or for further information, please contact Dr Sharmila Sumsurooah Sharmila.Sumsurooah@nottingham.ac.uk Funding
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theory, robust and optimal control, and physics-informed modelling, this research aims to bridge the gap between data-driven learning and dependable real-world autonomy. Aim You will have the opportunity
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orla.williams@nottingham.ac.uk for more information Funding support After a suitable candidate is found, funding is then sought from the University of Nottingham as part of a competitive process (this will cover
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Closing date: 27 February 2026 For further information please email Professor Chris Gerada (University of Nottingham) and Dan Walton (MTC). Facilities The MTC is an independent Research and Technology
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to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional
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support population-level prevention strategies. Further information: Applicants should have either a minimum 2.1 undergraduate degree in a relevant area (public health, epidemiology, economics, statistics