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environment with wide-ranging expertise spanning data-driven imaging, clinical science, molecular biology, bioinformatics, and biomedical engineering, all working together to improve atherosclerotic and
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. To meet the general entry requirements for doctoral studies, you must: Hold a Master’s degree in computer science, image analysis and machine learning, engineering, data sciences, applied mathematics
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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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) 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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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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of forests under climate change. The PhD student will work in the Forest Remote Sensing group at the Department of Forest Resource Management at SLU, collaborating closely with other engineers and scientists
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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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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
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these processes using large-scale population genomic data from modern-day and prehistoric humans. The PhD position is part of the The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS