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graphics, machine learning and graphics programming, as well as a good command of English. Knowledge of data science and deep learning is an advantage. You demonstrate good team spirit, interpersonal and
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experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and components to automate
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the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and
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the computational task: first-principles active-site descriptor models, high-throughput screening with machine-learned interatomic potentials, and a dedicated catalysis database. This position is ideal for a
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on an NIH-funded project investigating relationships between physical fitness-related measures, Alzheimer’s disease biomarkers, and cognitive function in cognitively normal older adults. The Postdoctoral
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research skills, and experience building reproducible analysis or simulation workflows; have demonstrable expertise in one of the following domains and the motivation to acquire working knowledge
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decision-making. They will have strong knowledge of machine learning research methods, excellent programming skills, and the ability to communicate complex ideas clearly to academic and non-specialist
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Cognitive Science, Medical Informatics, or a comparable quantitative discipline Proven hands-on experience working with LLMs, foundation models, multimodal AI systems, or related machine-learning technologies
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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the Computing & Engineering Department. The group is very dynamic, ambitious, well networked and delivers state-of-the-art research in a range of machine learning and data science topics, publishing research