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genetic profiles combined with imaging parameters, and artificial intelligence. Our ongoing research activities include genome-wide associations studies, development of eye-on-a-chip and patient-specific
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for the development of therapeutics. In this project, we will develop in vitro and in vivo imaging techniques to study ion transport in the kidney. In this project, you will: Establish novel kidney organoid models
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software in different MRI scanner environments. The development of an image-guided radioembolization procedure in phantoms, ex-vivo and in-vivo animal models. Determine safety and effect on image quality in
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medical imaging AI and integrate this to improve treatment of patients with liver tumors? In the AI-IMAGINE project we aim to develop AI with real clinical impact. Will you join our ambitious team? As a PhD
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to optimize research in the use of Artificial Intelligence (A.I.) in neuro-oncology imaging and generate relevant insights into the relation between A.I.-generated characteristics and outcome in neuro
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picture of glycosylation on MPL. Moreover, you will generate glycosylation gene knockouts using CRISPR-Cas9 gene editing in induced pluripotent and hematopoietic stem cells, followed by hematopoietic
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medicine, clinical technology, or equivalent. Experience with Geant4 or other relevant software tools used for dose calculations and treatment planning (e.g. Monte Carlo codes, image segmentation, Python