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computer vision method for medical image analysis principally in oncology or pathology, with a possible focus on generative AI, explainability, multi-modality. Candidate’s profile A good Bachelors degree
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the mechanisms of neurovascular coupling (NVC) in the human retina — a key physiological process whose early dysfunction is linked to Alzheimer's disease. The team has developed a new cellular-resolution imaging
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-spectral microscopy framework that extracts meaningful spectral information from a single image, by combining innovative optical system design with learning-based data processing. The research aims
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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are seeking a Ph.D. student to join our multidisciplinary team developing a radical solution for better detection and treatment that uses ultra-thin snake-like robots and advanced optical imaging techniques
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project. The project will also employ a PhD student at Lund University, focusing on developing hybrid architectures for deep learning-based image processing and methods for multimodal medical data. We will
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/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 packages
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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Join the IMAGINE open innovation lab community to accelerate innovation. As a researcher you will: Design and conduct research on metabolic MR imaging technologies, focusing on improving quality
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models (CNNs, Transformers, GANs) for PET and CT dose reduction - Work with raw PET/CT data, projection data, and reconstructed images - Perform quantitative image evaluation and clinical validation