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(e.g., tensor or multi-modality data). Work with other researchers and PhDs to develop AI applications related to image processing, computational imaging as well as computer vision. Lead a team of junior
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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16 Jan 2026 Job Information Organisation/Company Computer Vision Center Research Field Computer science » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application
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Science at The Technical Faculty of IT and Design invites applications for a fully funded PhD stipend in the area of Human-Computer Interaction, generative AI, creativity research and knowledge worker studies. The position
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-based vision (event cameras), we are recruiting a research and development engineer within our Computer Science (INFO) and Mathematical and Electrical Engineering (MEE) departments. In collaboration with
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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and analysing general Computer Vision methods, using real-world image data as a challenging experimental setting. Research focus The PhD will address open research questions in Computer Vision related
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of computer vision models is comfortable working in multidisciplinary research environments, where methods are applied to biological or real-world problems Qualifications The applicant must: hold a PhD in a
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, eligibility and submission rules available via this link: https://migrationtime.eu/phd-positions Where to apply Website https://research.ku.edu.tr/mirekoc/events-and-news/news/?detail=true&id=5c73a14
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attending an academic Bachelor’s degree in the scientific field mentioned above. Knowledge or experience (preferred) on machine learning or computer vision techniques, and interest in developing such skills