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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team-oriented interprofessional education to ensure a highly
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and privacy-preserving machine learning (e.g. proving model integrity or fairness without revealing training data) Scalable ZK-proof constructions for federated and decentralised AI pipelines Formal
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/ The research fellow will work closely with PI Patrick Rebentrost on developing novel quantum algorithms
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algorithms, and some knowledge of data science and machine learning (through coursework, self-learning, or personal projects). The selected student will work with Ph.D. and master's students to help develop
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embodied interaction); game design and development practices (e.g., XR, VR, computer graphics, and programming); and play in participatory, learning, and societal contexts (e.g., STEAM education and live
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, computer science, machine learning, or natural language processing, focusing on AI for Social Good or similar. Excellent written and spoken English is required, since the project is carried out in an international
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máquina/profundo aplicado al procesamiento de imágenes y vídeo / - Application of machine learning and deep learning techniques to image and video processing. - Aplicación de lo anterior al caso de uso
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modalities in the rodent brain (3D light-sheet microscopy, spatial transcriptomics and MRI of the same brain) to learn MRI contrasts that can depict neuronal and glial cell density and morphology. You will