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Computer Science, Biomedical Engineering, Pathology Informatics, or a related field, with emphasis on computer vision and machine learning (summer and fall graduates are also welcome to apply) Proficiency in
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. In addition, the nature of the interaction between human and machine triggers new questions about the locus of agency and learning these emergent collaboration ecologies. Such examinations may require
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modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
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at Northeastern. (10%) Required Qualifications: - Ph.D. in Human-Computer Interaction, Information Science, Computer Science, Design, or related fields - Strong record of published research in HCI, CSCW, DIS
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, China [map ] Subject Areas: Physics / Atomic Molecular and Optical Physics , artificial gauge fields , Cold Atom Physics , Condensed Matter Theory , Machine Learning , Quantum Hydrodynamics , Quantum
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machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role. This post would be ideal for an ambitious and
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approaches, machine learning) where appropriate. The successful candidate will actively promote FAIR data practices and will have opportunities to contribute to teaching, training, and wider community
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machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role. This post would be ideal for an ambitious and
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modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
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. Preferred Qualifications: Prior experience working with mouse models of cancer is strongly preferred; candidates without prior experience will be considered if willing to learn. Interest in tumor metabolism