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FieldComputer science » OtherEducation LevelPhD or equivalent Skills/Qualifications CANDIDATE ’S PROFILE The candidate should possess a PhD in machine learning or computer vision and have a strong publication
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profile PhD in Computer Science, Data Science, Machine Learning, or a related discipline. Proven experience in computer vision (e.g. image processing, deep learning, object detection, segmentation) and
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computing. You will join the Vision & Human-Robot Interaction (VHR) Group, which brings together researchers working at the intersection of computer vision, robotics, and assistive technologies. The team is
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computing. You will join the Vision & Human-Robot Interaction (VHR) Group, which brings together researchers working at the intersection of computer vision, robotics, and assistive technologies. The team is
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and implementing vision processing algorithms that enable robust robot tracking and autonomy. The ideal candidate will possess hands-on experience designing, implementing, and deploying computer vision
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postdoctoral researcher, you will be part of the computational component of the project. You will collaborate closely with the principal investigator, two PhD candidates (working in psycholinguistics and
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main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications
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Position: Postdoctoral Researcher in Vision-Language-Action Models and Physically Informed Neural Networks for Surgical Robotics Publication date: 30.09.2025 Closing date: 29.10.2025 Level of education: PhD
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Computer Science, Information Engineering, Computer Engineering, or related fields (or equivalent foreign degree). Candidates completing a PhD within 6 months may apply. Excellent English proficiency Up to 6
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Qualifications PhD in Robotics, Electrical & Computer Engineering, Mechanical Engineering, Biomedical Engineering, Computer Science, or closely related field. Must have PhD conferred upon hire. Preferred