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) classification and utilization based on advanced AI technologies, such as regenerative AI, image processing and reinforcement learning, that can improve the energy efficiency and reduce the operating cost and
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KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Project description Third-cycle subject: Computer Science This project involves generative modeling
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methods that use light to explore biological systems and processes at the molecular, cellular, and tissue levels. It includes experimental light microscopy and image analysis, such as super-resolution and
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include Drive research projects which include analysis of tissue images from multiplex immunofluorescence, spatial proteomics and transcriptomics Drive development of deep learning and computer vision tools
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biological basis, through technological processes and mathematical support. Your profile We are looking for a candidate with proficiency and documented research experience particularly in immunology and/or
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methods that use light to explore biological systems and processes at the molecular, cellular, and tissue levels. It includes experimental light microscopy and image analysis, such as super-resolution and
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Familiarity with large language models or multimodal systems An interest in visual reasoning, educational technology, or human–AI interaction Experience with neural networks for image or video understanding
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Admission to Doctoral (PhD) Studies in the subject Engineering Sciences with specialization in Biomedical Engineering at the Division of Biomedical Engineering, Department of Materials Science and
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institution affiliated with both the Faculty of Engineering (LTH) and the Faculty of Science at Lund University. Within the division of Computer Vision and Machine Learning, there are several senior researchers
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Master Programmes, at the Faculty of Medicine, and at the Disciplinary Domain of Science and Technology. The department has a yearly turnover of around SEK 500 million, out of which more than half is made