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for perceptual and creative relevance; Curate and/or utilize benchmark datasets of pareidolic visuals, and apply statistical and machine learning methods to analyze visual data and model behavior; Publish and
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the field of computer vision and with training, validating and inference processes in machine learning; Familiarity with generative AI; Curious about mathematics and biology; Excellent programming skills
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advanced motion planning algorithms with machine learning techniques, such as reinforcement learning, imitation learning, and task generalization. You will focus on designing intelligent robotic systems
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research within the scope of the project culminating in a successful dissertation, as well as writing academic articles and presenting your work on international AI and machine learning conferences
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the Department of Machine Learning and Neural Computing (MLNC) at the Donders Centre for Cognition (DCCN) and the School of Artificial Intelligence (AI), both part of the Faculty of Social Sciences of Radboud
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Your job Are you looking for a PhD position where you develop state-of-the-art machine learning methods for the life sciences (geometric deep learning, transformer-based approaches, ...) with a
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-GUIDE project, we will make directed evolution guidable and, ultimately, predictable by machine learning. Specifically, you will build a first-in-class framework to expedite the design of high-affinity
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant
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of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant for the new green steels compositions, including impurities and tramp elements. These models should enable
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Criteria A MSc degree in Computer Science, Statistics, Data Science, Artificial Intelligence, or a related field; Strong knowledge of and experienced with statistics, machine learning, and stochastic