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on computer vision. The role involves developing and advancing novel algorithms for emerging challenges in computer vision, including continual learning and few-shot learning. The candidate is also expected
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application! We are now looking for a PhD student in Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Your task will be to analyse and adapt vision
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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molecular docking, molecular dynamics and free-energy methods (MD/FEP), machine learning for molecular design, and protein–ligand modelling. Experience bridging computational and experimental groups, and the
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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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physics, electrical engineering, image processing, computer vision, AI, machine learning, data science, computer science, applied mathematics, or in a similar field, or have completed at least 240 credits
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different areas of AI (such as machine learning, computer vision, natural language processing, and bioinformatics), hosting powerful computing facilities internally and as part of the EU EuroHPC supercomputer
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to demonstrate documented proficiency in English. You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
); Relevant research experience in at least one of the following: Social Robotics, human-robot interaction, human-computer interaction, Machine Learning, Affective Computing, Social Signal Processing, Computer
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI