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Field
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learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In this role, you will
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of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In
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Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on
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generative AI, multimodal representation learning, and modelling face-to-face dialogues for our NWO-funded project “Grounded Gesture Generation in Context: Object- and Interaction-Aware Generative AI Models
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project from the Dutch Polymer Institute (DPI). The main objective is to develop and validate a real-time, AI-enabled multi-sensor fusion platform for diagnostics and prognostics of polymeric bearing cages
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Generation in Context: Object- and Interaction-Aware Generative AI Models of Language Use”. Preferred start date is 1 February 2026 but is negotiable. Face-to-face conversation is the primary setting for human
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settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on obtaining external funding and project
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problem-solving. The project has two main objectives: To design evidence-based interventions for each phase of the collaborative creative problem-solving process, grounded in the creative problem-solving
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Research Council Starting Grant and led by Dr George Iordachescu. The main objective of this research project is to radically transform understandings of how strict protection of nature remakes human
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George Iordachescu. The main objective of this research project is to radically transform understandings of how strict protection of nature remakes human-environment relations in Europe’s marginal areas by