540 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" uni jobs at University of Sheffield
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thermal analysis system in one of our Laser Sintering machines in the Advanced Polymer Sintering Laboratory here in Sheffield, which will provide novel insight into thermal effects within the process
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data acquisition. • Computational techniques, including machine learning and statistical inference. • Collaborative research at the interface of mathematics, biology, and physics. Why us? The
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physical systems. You will explore how the dynamic behaviour of nanomagnetic devices can be used to realise these KAN functions directly in hardware. Working with a combination of modelling, machine learning
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Digital and sensor based conformance validation for large scale forged components (C4-AMR-Crawforth)
intermediary data streams that can offer insight into how the component and manufacturing process is performing. Within both of the fields of forging and machining there are numerous industry-ready low-intrusive
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computer-based models of manufacturing process, allowing for analysis, optimisation and visualisation of operations before physical implementation. It is a sought after skill in many high-value manufacturing
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developing a computational model that simulates blood flow for ICH patients. The research will exploit a powerful new approach — physics- informed neural networks (PINNs) — that combines machine learning with
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design, process simulation, material characterisation, process monitoring and control, as well as post-processing techniques including heat treatment, machining and surface finishing. You will play a key
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AI-based diagnostics for fleet-based condition monitoring of electric vehicle motors using machine learning frameworks (S3.5-ELE-Panagiotou)
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Physics based machine learning algorithm to assess the onset of amplitude modulation in wind turbine noise (with TNEI Group)
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reducing the number of pixels used for the same region of interest and thus get a rather blurred image or c) acquire a sparse dataset where the electron beam has skipped certain (random) positions. Some