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To undertake research on the evolution of prokaryotic pangenomes using machine learning and AI approaches. The work will involve the analysis of large prokaryotic genome datasets, the development
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navigation algorithms and machine learning models on physical robot platforms. We are particularly interested in candidates with expertise in generative AI and curriculum learning applied to robotics, as
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Computer Science or a related topic. Applicants at the PDRA level must have a PhD in NLP or machine learning. Substantial knowledge of Natural Language Processing (NLP) and machine learning methods is essential, as
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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
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to develop a holistic e-motor cooling technology, maximising heat transfer through direct-contact, spray cooling. The Team is looking to appoint one Postdoctoral Research Associate on Machine-Learning Assisted
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develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung infection. As part of this work, the postholder will
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning methods for multimodal imaging and real-time analysis in
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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intelligence experts to generate new projections of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet