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Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated researcher to join our cutting-edge project on AI tool
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) are looking for a: PhD Candidate on Multi-Objective Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated
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faces. At the same time, reinforcement learning is a key technology in artificial intelligence and machine learning that set various state-of-the-art results. In the Reinforcement Learning Lab
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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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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
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modelling, and an ability to learn new concepts and (computational) methods as needed Affinity with scientific computer programming (e.g., R, Matlab, Python) Proficient communication skills in spoken and
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combination of tomographic imaging and machine-learning based techniques. You will work with real data gathered from museum collection objects and will also design your own experiments to gather insights in
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, Physics, or a related field; Good knowledge of and experienced with machine learning; Good knowledge of and experienced with Image processing techniques; Highly motivated to both perform foundational
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project will be to develop novel image acquisition schemes and image reconstruction algorithms for using a combination of tomographic imaging and machine-learning based techniques. You will work with real