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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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, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental aptitude is desirable.
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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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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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European Centre for Environment and Human Health in the Faculty of Health and Life Sciences at the Penryn Campus in Cornwall. Measures taken in the built environment to reduce energy consumption (to help achieve net zero goals) can impact on the indoor environment and have positive or negative...
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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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discover therapeutic targets relevant to Welsh populations. You’ll also help translate your computational insights into lab-based validation using experimental models, paving the way for new diagnostics and
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student will take advantage of state-of-the-art soft polymer fabrication (3D/4D printing) and characterisation (i.e. electro-mechanical multi-axial testing rigs) equipment and the latest computational
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the Computational Foundry, a world-class centre for computational research, part-funded by the European Regional Development Fund through Welsh Government. The brand-new building of the Computational Foundry provides
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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