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Field
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environments that aims to address how distributed sensing, fibre-optic monitoring, environmental observations, drone- and satellite-based data, operational infrastructure datasets, and/or machine learning can be
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fluid mechanics, computational geometry, meshing, computational graphics, computational vision, or scientific machine learning in general. Successful candidates will join a community of researchers in
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow, Machine Learning Department Cooper Laboratory | Department of Orthopaedics | Faculty of Medicine (Anthony Cooper
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, including parsing and processing large document corpora. Strong understanding of machine learning or AI methods applied to health or biomedical data. Demonstrated ability to assess model outputs, identify
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 2 months ago
& Medicine. This is an exceptional opportunity for a talented and ambitious researcher to build an independent, high-impact research program at the intersection of machine learning and healthcare
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the shallow subsurface (<10 meters depth). Experience with soil moisture/salinity and sapflow sensors. Experience using neural networks and machine learning tools. Stipend $70,000.00 – $80,000.00 Yearly Point
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in machine learning and/or computer vision as applied to robotics. - Strong publication record and demonstrated research independence. The referenced salary range is based on Johns Hopkins University's
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duties as assigned. REQUIREMENTS: REQUIRED: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong programming skills. Strong background in machine
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equipment or related technologies artificial intelligence, machine learning, image analytics, computer vision or related computational approaches applied to healthcare research (desirable) a peer-reviewed
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mathematical structures and computational algorithms underlying modern machine learning and artificial intelligence. Relevant themes include geometric and algebraic methods for learning, structure-preserving