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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
motivated candidate with a strong interest in machine learning and clinical neuroscience. The lab studies resilience and vulnerability in brain aging and dementia, and builds computer-aided methods and tools
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signals, imagery, and natural language, via adaptive machine learning; 2) Personalization of sequential decision making, biophysical digital twins, and the operation of digital and physical systems; and 3
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analysis, and data visualization. Apply advanced statistical, machine learning and AI methods when appropriate. Review analysis outputs and ensure methodological consistency and quality. Collaborate with
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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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Science, or a closely related field. Strong theoretical background in machine learning with proven experience in applying reinforcement learning to practical, applied problems. A clear interest in human health
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atomistic simulations, scientific machine learning, reaction modeling, and integration of computational and experimental data. The associate will develop reproducible computational workflows, collaborate with
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collection, data engineering, statistical modeling, or computational text and image analysis; Machine learning, natural-language processing, large language models, or evaluation and auditing of AI and online
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. Beyond Discrete Mathematics, the Department of Mathematics and Mathematical Statistics carries out research in computational mathematics, financial mathematics, mathematical modeling, analysis, machine