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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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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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“Dynamics of Soil Processes” at the University of Hamburg, and also work closely with the junior research group “COLDSPOT”. PeTCaT aims at closing key knowledge gaps and at reducing uncertainties in carbon
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. Strong background in neuroimaging techniques (e.g., MRI, PET) and computational modeling. Proficiency in programming languages such as Python, MATLAB, or R. Experience with image processing tools and
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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
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to explore the regulation of mRNA modifications in developing cortical neurons. Key techniques will include biochemical approaches, fixed tissue imaging, stereotactic surgery, structural and functional
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collaborative programme bringing together a team of leading experts in advanced electron microscopy imaging, first-principles modelling, metal halide semiconductor thin-film and device fabrication, and
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thermochemical reactor process for heat storage, characterizing its behaviour and thermal performance. Post-doc Objectives: A prototype, representative in scale of the final system (several kW and several kWh
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Hospital. The position focuses on advanced medical image analysis in musculoskeletal medicine, with opportunities to take on scientific leadership responsibilities. The AIO group is part of the Department
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their own research questions and lead projects. Experience in neuroimaging (particularly functional) is required, and ideally the candidate will have experience in linking imaging methods with cognitive