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Field
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Department of Ancient Civilizations of the University of Basel invites applications for one PhD
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The Department of Ancient Civilizations of the University of Basel invites applications for one PhD student position (100%) in Computer Vision for 3 years on the topic of offline to online
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of novel computer vision methods capable of robustly detecting AUs. Next, the focus will be on novel AI methods for classifying normal vs. pain vs. stress faces. Lastly, head pose detection of horses in
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Professor Richard Bowden once deadline passes. You will need to meet the minimum entry requirements for our Vision, Speech and Signal Processing PhD programme. Please note: This opportunity is also open to
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University of Strasbourg - ICUBE Laboratory (UMR7357) | Strasbourg, Alsace | France | about 2 months ago
PhD positions open in the CAMMA research group, Strasbourg, France. They aim to develop novel computer vision/artificial intelligence approaches to analyze surgical activities in videos at scale using
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14 Mar 2024 Job Information Organisation/Company Computer Vision Center (CVC) Research Field Computer science Researcher Profile First Stage Researcher (R1) Country Spain Application Deadline 30 Jun
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14 Mar 2024 Job Information Organisation/Company Computer Vision Center (CVC) Research Field Computer science Researcher Profile First Stage Researcher (R1) Country Spain Application Deadline 30 Jun
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Programme? Not funded by an EU programme Reference Number PHD GSO 007-24 Is the Job related to staff position within a Research Infrastructure? No Offer Description Application(s) are invited from suitably
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projects Prior experience in computer vision, image analysis, or machine learning Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow or PyTorch Prior
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welfare. This PhD aims to deploy cutting-edge computer vision algorithms alongside veterinary insights to monitor and improve dairy cow health and welfare outcomes accurately and automatically. Successful