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: analytical and forensic science; asthma and allergy; biophysics and cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering
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sponsorship. Qualifications Required qualifications PhD in biomedical engineering, electrical engineering, or equivalent engineering degree with an in-depth understanding of physiological signals in response
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applications ranging from next-generation laser technology and precision material processing to laser-driven self-assembly and surgery, all the way to a long-term vision of developing an “Atom Printer” based
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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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engineered animal models, single-cell profiling, and advanced image processing and analysis. In addition, numerous institutional shared resources and core facilities support the laboratory by providing
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for astrobiology and astrochemistry. Your profile A qualified candidate will have a PhD in electrical engineering, physics, or a related field, as well as expertise in one or more of the following: nanofabrication
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Computational Color Research, Image Processing, Computer Vision. Knowledge of latest generative architectures Good programming skills using Python Other merits Experience superior to that required in similar
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. Publish and present findings in international journals and conferences. Supervise and mentor junior researchers and students. Profile PhD in Computer Science, Biomedical Engineering, Data Science, or a
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references - Representative publication (can be a preprint or in prep) Required skills/qualifications: - A PhD (by start of employment) in Psychology, Neuroscience, Biomedical Engineering, Cognitive Science
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image reconstruction methods, signal processing techniques, and data analysis pipelines for novel X-ray imaging modalities, including ghost imaging, quantum-enhanced imaging, and other correlation-based