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practical applications, including solving mathematical reasoning problems. The ideal candidate has a strong background in machine learning and an interest in bridging rigorous theoretical insights with
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Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical
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techniques and machine learning algorithms. The goal is to decipher patterns in the bioelectrical signals. Project UID-50008-2025 funded by FCT-Fundação para a Ciência e a Tecnologia. Scientific Area: Basic
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will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato, other members of the Cambridge Machine Learning Group (mlg.eng.cam.ac.uk ) and
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well as machine learning techniques, is central to our mission: Development and application of advanced simulation techniques to explore and identify the fundamental structures and mechanisms occurring in
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. This PhD project aims to create advanced XCT workflows by developing Artificial Intelligence (AI) and Machine Learning (ML) tools to support imaging before the reconstruction phase. The research will focus
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Description Your Responsibilities We are looking for a highly motivated PhD student in the areas of Probabilistic Machine Learning and Neuro-Symbolic AI to contribute to the Cluster of Excellence “Bilateral AI
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industry and academia together to drive pre-competitive, fundamental research in polymers. We welcome applicants with interests in polymer physics, materials processing and characterisation, machine learning
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different areas of AI (such as machine learning, computer vision, natural language processing, and bioinformatics), hosting powerful computing facilities internally and as part of the EU EuroHPC supercomputer
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PixHawk Autopilot, Arduino boards, Raspberry Pi - or equivalent Experience with ROS/ROS2 Experience with programming languages like Matlab, Python, C++ Familiarity with machine learning and/or deep learning