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Teesside University); (3) nature and natural heritage (the focus of a matching post based at Newcastle University); (4) active evaluation for learning (e.g. research conducted by team members, serving as
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Nuffield Department of Clinical Neurosciences (NDCN), MRC Brain Network Dynamics Unit, Mansfield Road, Oxford The post holder will develop computational models of learning processes in cortical
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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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degree (or near completion) in Electrical Engineering, Computer Science, or a closely related subject. Research experience in wireless communications and deep learning is essential. The project will also
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teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate about groundbreaking international research and
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degree (or near completion) in Electrical Engineering, Computer Science, or a closely related subject. Research experience in wireless communications and deep learning is essential. The project will also
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capabilities o Demonstrated experience with machine learning and/or statistical modeling o Expertise in handling large-scale, complex datasets with strong data wrangling skills o Strong publication record
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quantify vulnerabilities in current AI systems Excellent academic writing and communication skills Strong coding skills in at least one of MATLAB, Python, C, and experience with, or willingness to learn
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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 learning them where relevant to the project. The appointed person will be required to carry out up to two months of fieldwork every year, produce their own and co-authored publications, co-organise