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topics: Development of deep learning models Mathematical foundations of machine learning Optimal deployment of AI systems The candidate is expected to hold a relevant MSc degree in Computer Science
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algorithmic and theoretical foundations of reinforcement learning applied to complex, high-dimensional dynamical systems. The project focuses on the intersection of deep reinforcement learning
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Track Record: At least two first-author research papers at flagship venues of core machine learning research (e.g., NeurIPS, ICML, ICLR, AISTATS). Theoretical Rigor: A deep understanding of
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Biotech Research and Innovation Centre, The Lund Group, University of Copenhagen | Denmark | about 1 month ago
project is conducted in collaboration with the deep probabilistic programming group of Thomas Hamelryck: https://di.ku.dk/english/research/groups/machine-learning-in-biology/?pure=en/persons/271052
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, Department of Health Science and Technology, one or more PhD stipends in Unsupervised Learning for Medical Image Analysis are available for appointment from November 1, 2026, or as soon as possible thereafter
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-motivated-language-model-security/ , and an Erasmus+ project on AI-based Personal Language Learning Assistants in collaboration with VSKDansk https://www.brondby.dk/om-kommunen/nyheder/2025/08/vskdansk-far
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associate professor positions at the Department of Sports Science and Clinical Biomechanics in general, please click . Qualifications Candidates with the following competencies will be prioritized: A PhD
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, adapt and use deep learning methods for analyses of omics-based data obtained in the project. Collaborate with international partners and contribute to joint research efforts within the program
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emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods for analyses of omics-based data obtained in the project. Collaborate