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Employment 0.8 - 1.0 FTE Gross monthly salary € 3,546 - € 5,538 Required background PhD Organizational unit Faculty of Science Application deadline 04 January 2026 Apply now Are you curious about
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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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affects the performance of plasmonic structures in photovoltaics and imaging. About this position In this position you will leverage materials with high thermal conductivities (e.g. 2D materials) to achieve
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will image them using a variety of microscopy methods, and collaborate with a team of computer vision scientists to build ML-based models for phenotype prediction, helping to accelerate the cell
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cell lines have been engineered and characterised, you will image them using a variety of microscopy methods, and collaborate with a team of computer vision scientists to build ML-based models
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(GenIR), a new and rapidly evolving retrieval paradigm where generative models are used to directly generate document identifiers given a user query. This paradigm departs from traditional multi-stage
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generate document identifiers given a user query. This paradigm departs from traditional multi-stage retrieval pipelines and instead integrates the indexing and retrieval process into a single, end-to-end
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play a key role in the integration and analysis of omics data collected within the groundbreaking TREAT EARLIER trial. This trial is the first preventive study in the field of rheumatology globally and
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applications involving image analysis, real-time monitoring, or complex process optimization. You have hands-on experience with model optimization techniques such as post-training quantization (PTQ
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and document analysis. Explore what data are available on essential health resources and supporting systems, and assess their usefulness. Co-create a regional risk picture by facilitating workshops