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or equivalent in physics or other cognate area of relevance to the post. Hold or about to obtain a PhD in a relevant area (e.g. Physics). Significant relevant experience in the in the following areas: The theory
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strong background in relevant areas. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and/or publications as required by
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 9 hours ago
Department College of Engineering (Col) Work Unit Albert School of Construction Work Location Smith Building Vacancy Open To All Candidates Position Designation Post Doc Employment Type Temporary - Full-time
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effective? The project is aimed at technical innovations in computational physics and computer vision (sensing, camera calibration, depth estimation, tracking and visualisation) to enable real-time tissue
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 months ago
research activities will be hosted at i3S, under the scientific coordination of Doctor Daniel Ferreira. Length time: The duration of the fellowship is 5 months and 15 days and the expected starting date is
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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs
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Posting Details Position Details Title Postdoctoral Fellow - Nephrology Specific Title Appointment Type Postdoctoral Fellow Department IUSM - Medicine - Nephrology Campus IU School of Medicine
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effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several
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positive attitude and drive for learning skills, methods and theory • Ability to work in a structured manner, facilitating teamwork • Ability to prioritize and complete work tasks Employment in
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simulations combined with physics-informed machine learning will also be examined. Several research and industrial partners are a part of this project. The ideal candidate would combine strong computational