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and planning status Onboard Processing of Hyperspectral Imagery: Deep Learning Advancements, Methodologies, Challenges, and Emerging Trends Onboard Processing of Hyperspectral Imagery: Deep Learning
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(analysis/ geometry), applieddifferential geometry and machine learning;•Solid publication record in image analysis, scientific computing or machine learning.•Knowledge and practical experience in at least 3
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learning approaches for both image analysis and experimental design Strong competencies and demonstrated commitment to FAIR data management, organization, and reproducible research practices Excellent
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Vacancies Postdoc position on reinforcement learning on real-time image/video processing for medical robot Key takeaways In this role, you will be responsible of developing cutting-edge deep
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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine learning models without moving sensitive or large
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Radboud University Medical Center (Radboudumc); 10 Oct ’25 published | Netherlands | about 1 month ago
Image Analysis Group (DIAG) at Radboudumc. We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided
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Vacancies Postdoc position on deep learning based medical imaging for medical robot Key takeaways In this role, you will help develop and implement cutting-edge AI solutions for real-time, image
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team of experienced researchers in imaging, machine learning, oncology, and pathology. We do not discriminate on the basis of sex, gender, belief, culture, place of birth or occupational impairment when
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mathematical modelling, with a focus on real-world applications. This includes statistics, uncertainty quantification, data analysis, signal processing, (mathematical foundations of) machine learning, and