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for data-efficient vision foundation models. Foundation models in computer vision currently rely on massive datasets and brute-force scaling. This leads to high data requirements, hidden biases, limited
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models for high tech industry applications. Your results are expected to be published at leading international venues in machine learning, computer vision, robotics and radar, such as NeurIPS, CVPR, ICRA
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are seeking a PhD candidate for a 4-year contract to develop and apply computational models and video-based tools to capture hand movement and function with deployment in the home environment as the target
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vision, robotics and radar, such as NeurIPS, CVPR, ICRA, IEEE IV and RadarConf. For your research, you will have access to extensive computing resources at TU Delft, ranging from personal workstations and
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) Application Deadline 1 Nov 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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technology be designed and evaluated so that it is usable, acceptable and aligned with users’ communication preferences and everyday lives? Your role Your PhD will primarily focus on computer vision and
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at the intersection of computer vision, micro-electronics analysis, and hardware security, and will work under the supervision of researchers within the Department of Intelligent Systems. The PhD researcher will be
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Welcome to Maastricht University! How can coaching better support young
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hours per year (based on fulltime) and extra holidays between Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; a complete educational program for PhD students
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1 January; multiple courses to follow from our Teaching and Learning Centre; a complete educational program for PhD students; multiple courses on topics such as leadership for academic staff; multiple