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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
the theoretical foundations of data science and AI. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and
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development of advanced cryogenic calorimeters and associated electronics for the next-generation neutrinoless double-beta decay search. Support the development of Artificial Intelligence (AI) algorithms
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was created to advance research in the mathematical, algorithmic, and statistical foundations of data science and their application to other disciplines. In addition to providing support to core foundational
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). Design and fabrication of the calibration test phantoms Developing and testing acquisition software, and implementing image analysis algorithms and localization methods. Where to apply E-mail
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in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems tailored to dynamic, human-centered environments. They may
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
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are especially encouraged: (1) statistical mechanics, condensed-matter theory, quantum field theory; (2) tensor networks, quantum information, quantum algorithms; (3) machine learning, generative models, large
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machine learning techniques to raw ultrasound data. The project involves developing novel algorithms that integrate physics, engineering, and AI to extract meaningful and clinically relevant information
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understanding of the interactions between communication, sensing, control, and decision-making in autonomous robotic systems. Experience in developing algorithms for robot navigation, path and trajectory planning
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, and development of algorithms for real-world clinical data. The fellow will have the opportunity to work with clinicians, engineers, data scientists, trainees, and research staff in a highly