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an exceptional opportunity to conduct cutting-edge research at the intersection of machine learning, healthcare, and computational modelling, contributing to real-world clinical impact. What is offered
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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the genetic factors influencing changes in brain structures, using brain imaging, computational and statistical methods of network science. Project Aim: The aim of the project is to uncover the complex
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clearance level. The Engineering Doctorate Researcher will follow the EngD in Model-Based Systems Engineering Programme. They will be based at NPL. Entry requirements: A minimum of an upper-class honours
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, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental aptitude is desirable.
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the PhD in Engineering programme. Make sure to reference the supervisor's name (Dr Farzad Hayati) in your application. Informal enquiries are welcome and should be directed to Dr Farzad Hayati at f.hayati
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programme. Details of how to apply for the PhD programme are available at this page: https://www.sheffield.ac.uk/postgraduate/phd . When you apply, you should include the supporting documents relevant
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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candidates with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different