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- Delft University of Technology (TU Delft); Published yesterday
- Delft University of Technology (TU Delft); yesterday published
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- Delft University of Technology (TU Delft); Published 11 Nov ’25
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- Delft University of Technology (TU Delft); today published
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- Radboud University Medical Center (Radboudumc); 10 Oct ’25 published
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fibrosis. Together with the department of surgery, focusing on vascular surgery, we aim to to ulitse high-throughput biomaterial screening to identify the optimal physicochemical surface properties
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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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working on XAI and metadata creation, including both image and text analysis. You will organise benchmarks that assess AI technologies, particularly in the domain of newspapers, both current and historic
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how chromatin influences the mechanical properties of the nucleus? And do you enjoy integrating biophysics, cell biology and quantitative imaging to answer fundamental questions in biology? Then this
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aims to study how the brain processes pictures and sequences of pictures, like in comics. These PhD positions will study how sequences of images combine images together into hierarchic relationships
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to functionally validate our proteomics discoveries with in vitro phenotypic assays and microscopy imaging. For this position, we seek a highly motivated biochemist or analytical chemist with proven expertise in
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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