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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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characterization of the obtained optical fibers (loss, bend sensitivity, modal quality, polarization, etc.). - Geometric measurements of fibers (surface roughness, transverse profile, SEM imaging, etc
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, electrophysiology, imaging, genetic and whole-animal cardiovascular assays. This position represents an opportunity to work side-by-side with talented graduate students, postdocs, and specialists in a dynamic and
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for ICT researchers. Technical and project management development supports will be provided through prototype development, project management, and guidance on operationalising systems. Finally, the Hub will
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cell lines and primary cells. Technical support in fluorescent microscopy acquisition. Managing Image processing and analysis of live imaging microscopy acquisitions. Basic requirements of the position
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accreditation • Proven experience working with animal models • Extensive expertise in histological and imaging techniques, including confocal microscopy • Proficiency in image analysis software (e.g., ImageJ
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automated liquid handling systems and robotic workflows for running high-throughput experiments and processing large datasets. Desired qualifications Knowledge of various screening strategies (in vitro and in
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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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) Extrapolation of photospheric magnetic fields to the corona using various approaches. 2) Quantitative analysis of HXR (imaging spectroscopy from STIX and HXI) and EUV (fluxes and DEMs) sources. 3) Analysis and
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics