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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 foundation. Candidates are also expected to have strong coding and implementation skills, with the...
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applications, including solving mathematical reasoning problems and tackling the Abstraction and Reasoning Corpus (ARC) challenge among others. The ideal candidate has a strong background in machine learning and
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, neuroscience, machine learning, or related fields and/or merit/distinction-level performance in a relevant postgraduate degree (e.g. MSc) Experience of working in a neuroscience, clinical or engineering research
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Project Title: Intrinsically-aligned machine learning In a truly cross-disciplinary effort, this project, funded by the Leverhulme Trust and in collaboration with the University of Manchester, will leverage
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
with setting up a streamflow forecasting system in Portugal and the advancement of scientific knowledge in machine learning probabilistic hydrological forecasting and decision-making optimized to act on
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optimization – with rigorous theoretical analysis. The ideal candidate has strong machine learning and AI expertise and is comfortable with – or eager to learn – large-scale multi-GPU experimentation
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programme , and is led by profs. Alexey Lyulin, Heiner Friedrich and Henk Huinink (all TU/e) and prof. Bernard Geurts (U Twente). The project explores how waste products can be turned into a sustainable
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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machine learning processing of the spectroscopic data • The optical design and development of novel custom spectroscopic sensors benefitting from freeform optics. • Integration of the in-situ