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and prosthetic devices in the real-world. This PhD project offers the opportunity to work on pioneering research that combines state of the art computational modelling (deep neural networks) and
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; Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | 7 days ago
Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) approach was recently developed to model such intersectional inequalities. This PhD will involve developing and applying the MAIHDA
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26th May 2025 Languages English English English The Department of Structural Engineering has a vacancy for a PhD Candidate in Multiscale modelling of grain boundary failure in high-strength
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. Although there is a clear synergy between fatigue damage and corrosion, most fatigue prognosis models do not explicitly consider the role of the environment, which is usually reduced to obscured fitting
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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
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. The group is world-leading in modelling of the ice sheet surface including firn, and maintains a dedicated network of automatic weather stations. Currently, our research group has 6 staff members, 8 Postdocs
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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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ships, such as combustion engines, fuel cells, and hybrid or electrified drivetrains. Experimental and modeling activities related to energy converters, fuel sustainability, and environmental impact
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programme at the University of Cambridge, focusing on modelling exoplanet interiors and atmospheres. The successful candidate will join a vibrant team led by Oliver Shorttle, the Planetary Chemistry group
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15th June 2025 Languages English English English The Department of Energy and Process Engineering has a vacancy for a PhD Candidate in Scalable Model Predictive Control for the Space-Heating