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and application of advanced computed tomography methods, with a focus on photon-counting CT, quantitative image analysis, and machine learning. The position will involve work across several NIH-funded
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machine learning, topological quantum materials, and/or related areas. The successful candidate will have access to HiPerGator, the fastest university-owned supercomputer in the United States (TOP500
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. The successful candidate will play a key role in designing and implementing research at the intersection of sensor data collection, machine learning, remote sensing, and real-time agricultural decision-making
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interpretable machine-learning models, including approaches for uncertainty quantification, model calibration, and transferability. The Postdoc will also contribute to the development of reproducible
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states, tissue organization, and biological programs, and connect these representations to mechanisms of human disease. Your work will sit at the intersection of machine learning, computational biology
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near completion of) in Machine Learning or Maths. Informal enquiries may be addressed to [email protected] For more information about working at the Department, see www.eng.ox.ac.uk/about/work
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genomics, population genetics, and machine learning. The successful candidate will contribute to method development, software dissemination, and scholarly publications. Duties and Responsibilities Lead
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/DPhil in robotics, computer science, machine learning, informatics, AI, or a closely related field. You will have an excellent academic track record in topics relevant to locomotion and manipulation; path
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further areas are also within scope, and we expect the candidate to contribute to at least one: 3D shape analysis and geometric machine learning. Learning on meshes, point clouds, and landmark
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incorporate machine learning techniques and has direct applications for array optimization and AMOC transport estimation. Research Environment The position based at the Rosenstiel School of Marine, Atmospheric