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application of AI and machine learning models to interpret complex X-ray datasets, and the integration of experimental and computational insights to generate actionable knowledge that advances sustainable metal
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programme focused on applying AI‑driven analysis to in situ advanced microscopy of fibre‑based materials. The project aims to develop and deploy machine learning tools that extract real‑time structural and
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investigating how dopaminergic and serotonergic systems interact in the primate frontal cortex to support learning and decision making. About the department The Department of Experimental Psychology is a large
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of applying them to data. Collaborative endeavours with members of the IPMU and Oxford groups is highly encouraged. You will have the opportunity to teach. Applicants should have a PhD (or close to completion
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the role The PDRA will carry out research on probabilistic circuits (PCs) and tree-based machine learning methods for generative modelling, with a particular focus on responsible AI. The project builds
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thrusts within the lab’s multi-agent security programme. You should possess a completed PhD/DPhil (or thesis submitted by the start date) in Computer Science, Machine Learning, AI, Security, Robotics
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to work on the discovery of new superconducting materials with high critical temperatures, using novel methods and concepts such as machine learning and quantum geometry. The project is related to large
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interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Christopher Summerfield. The post-holder will have responsibility
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are seeking a postdoctoral research associate to contribute to an innovative EU Pathfinder project at the intersection of polymer chemistry, molecular dynamics simulations, and machine learning. The primary
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agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 30.06.2032 Reference no.: 5374 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom