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-depth expertise in Computer Vision and Photogrammetry. - Mastery of state-of-the-art Neural Rendering (NeRF, NeuS, SDF). - Knowledge of Photometric Stereo methods. Operational Skills: - Advanced
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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industry. Job Title Postdoctoral Fellow – College of Computing Job Description The Data Intelligence Group at UM6P-CC is seeking two postdoctoral fellows in machine learning who will support the group’s
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, United States of America [map ] Subject Area: Computational Science / Artificial Intelligence/Machine Learning Appl Deadline: (posted 2025/11/19, listed until 2026/01/26) Position Description: Apply Position Description
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to the 30th September 2026. We are looking for outstanding machine learning researcher to join the Torr Vision Group and work on AI Scientists: systems that use foundation models, AI agents, and robotics
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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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techniques—including vision-language architectures (e.g., CLIP, BLIP), fine-tuning large language models for clinical NLP, and self-supervised contrastive learning—the models will learn to effectively combine
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Computer Science, Engineering, Mathematics, or a related field with a focus on machine learning, security, or formal methods. Strong publication record in top-tier conferences or journals in AI security, adversarial
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lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning techniques—including vision-language architectures (e.g., CLIP
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will