49 postdoc-in-distributed-systems-and-controls PhD positions at University of Nottingham
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A continual learning approach for robust robotic control in electric batteries assembly. This project is an exciting opportunity to undertake industrially linked research in partnership with
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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control of the electrical power system for aircraft applications, ensuring system stability across a wide range of nonlinear loads and operating conditions. Aim You will have the opportunity to research and
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challenges to the electricity transmission and distribution system, as solar power is not dispatchable and therefore its incorporation as a major element of the generation mix requires the accurate prediction
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4-Year PhD Studentship: Deciphering how domain organisation regulates heparan sulphate function Supervisors: Prof Cathy Merry, Prof. Kenton Arkill, Dr Andrew Hook Closing Date: 15 July 2025 Overview
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successes and proposes intelligent sensing and control solutions for automated robotic systems capable to be tele-operated using smart human-machine interfaces. This is an exciting PhD project that has a
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workspaces under positional restrictions. Develop smart control algorithms that will allow the robotics end-effectors to communicate with the central control system and coordinate tasks with other end
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EPSRC Centre for Doctoral Training (CDT) PhD in Digital Metal with BAE Systems (Enhanced Stipend) Solid-state Additive Manufacturing of Nickel Aluminium Bronze alloys Background UK Applicants
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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. This project will build upon our research and industrial successes, focusing on developing control solutions for automated robotic systems that can be teleoperated using intuitive human-machine interfaces