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Stig Brøndbo 18th January 2026 Languages English English English Faculty of Science and Technology PhD fellow in “LLMs based Knowledge Graphs towards Digital Twin Development in Green Shipping
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specimens for microscopy essential but could be taught. Additionally, assistance to the PI (MD) and a research scientist (Phd) in grantwriting and manuscript writing may be asked. QUALIFICATIONS: Minimum 2
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guidance and robotics. Our work combines medical imaging, computer vision, and machine learning with strong clinical translation, in close collaboration with Balgrist University Hospital and the national
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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of areas, including AI and machine learning, cloud and mobile computing, computer system and information security, evolutionary computation, computer vision and graphics, and bioinformatics
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support in developing grant applications and teaching resources. For more information about LIACS, see http://www.cs.leiden.edu What you bring PhD degree in Computer Science or a similar field; An academic
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, Vision, and Culture can be found at https://ung.edu/about/mission-vision-values.php Offers of employment are contingent upon completion of a background investigation including a criminal background check
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Associate Professor, Tenured Canada Impact+ Research Chair, Human Mobility and Wearable Technologies
performance through new wearable technologies and AI-powered movement analyses. This vision will be realized through collaborations with the Department of Computer Science and the Yousef Haj-Ahmad Department
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). The candidate will also be co-hosted by the KB, the National Library of the Netherlands (https://www.kb.nl/ ). Job requirements The successful PhD candidate will have: Master's degree (or equivalent) in
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, interdisciplinary research group with extensive international collaborations and access to large, high-quality clinical datasets. About us The Computer Vision Group at the Department of Electrical Engineering