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Field
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sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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at leading international conferences and publish in top-tier journals. The successful candidate will gain advanced expertise in multi-sensor fusion, signal processing, machine learning, and positioning
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Electrical and Electronic Engineering Department, Imperial College London PhD Studentship in Damping of IBR-induced Oscillation Position Summary: Applications are invited for a PhD studentship, to
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Max Planck Institute for Solid State Research, Stuttgart, Hamburg, Halle, Dresden | Dresden, Sachsen | Germany | 18 days ago
has an open call for multiple fully funded PhD student positions. Deadline for submission of your application is December 10th 2025! Five Max Planck Institutes (Dresden, Hamburg, Halle and Stuttgart
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to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront
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species, and the emergence of previously unseen classes. Recent advances in remote sensing and machine learning provide new opportunities to address these challenges, but most current approaches
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, temperature, CO2) conditions from pole-to-pole. This work will be done at UEA. Training The PhD candidate will acquire skills from the bench (e.g., PCR, cloning, phenotyping) to bioinformatics (e.g., Phython
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-627 Marie Curie Grant Agreement Number 0 Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for 1 dynamic and motivated full-time PhD student
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-disciplinary PhD project aims to provide a clear picture of the landscape of battery manufacturing, waste and end-of-life processing. The project aims are to: Identify waste streams and energy requirements