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Comprehensive Approach to Justification, Optimisation, and Education”), a European Union-funded research project aimed at improving the quality and radiation safety of medical imaging in children, adolescents
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Development of a Low-Voltage Multi-Beam SEM for High-Throughput Imaging | TU Delft Job description Scanning Electron Microscopy (SEM) plays a central role in today’s nanoscale imaging across both science and
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. PhD Candidate Neuroimaging in Epilepsy Our goal: to leverage advanced Magnetic Resonance Imaging (MRI) techniques (including functional MRI to assess brain network metrics and MR spectroscopy to measure
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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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tracers. Specifically, you will use clinical molecular imaging data in combination with numerous methods (i.e., AI image analyses, PBPK modeling, immunohistochemistry, FACS). As a postdoctoral researcher
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GenAI for reproducing, modularizing and FAIR publication of existing research. The reproducibility of scientific findings often depends on access to workflows and code used in original analyses. However
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You will develop and validate advanced AI models that integrate medical imaging, multi-modal clinical and omics data, and explainable AI (XAI) for the prediction of hepatocellular carcinoma (HCC
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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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(e.g., PyTorch, TensorFlow, JAX), and scientific libraries (e.g., NumPy, SciPy, scikit-learn) Familiarity with medical images such as x-ray, CT, or fluoroscopy. Proficiency in Python coding language and
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of images (like in comics) in relation to the structure of languages. Additional information about this research project can be found at www.visuallanguagelab.com/pictree . Your position The PICTREE Project