492 machine-learning-and-image-processing-"RMIT-University" PhD positions in United Kingdom
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candidate will have strong analytical skills and substantial experience in machine learning at scale. The Prorok Lab in the Dept. of Computer Science & Technology, has a variety of robotic platforms (aerial
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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the combined themes of human-computer interaction and critical computing. The lab will be exploring the notion of "deceptive by design" on all fronts: social identity cues in the design of LLM-based chatbots
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This
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machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens
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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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A fully funded 3.5 years PhD position in the field of experimental nanoscience at surfaces and molecular imaging of conjugated polymers is available in the group of Prof. Giovanni Costantini at UoB
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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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fantastic opportunity for ambitious computer scientists to join our Computer Science Graduate Teaching Assistant (GTA) Programme! How does it work? Candidates will study for a four year, full time funded PhD