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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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understanding of complex immune–tumour molecular engagement. Your job In recent years, we have developed new proximity-based proteomics methods to investigate protein signaling dynamics between cytotoxic immune
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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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recruiting a postdoctoral researcher in AI for fluid mechanics. This postdoc is part of an NWO-funded project on accelerating computational modelling of rarefied (i.e. highly dilute gases), which brings
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work at the interface of molecular biology, cell models of the blood–brain barrier, and advanced human in vitro systems such as induced pluripotent stem cell (iPSC)-derived cultures and organoids. A key
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aging-associated mechanisms and the development of RNA therapeutics for the brain. The successful candidate will work at the interface of molecular biology, cell models of the blood–brain barrier, and
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their involvement in disease resistance under controlled conditions. Our model system is the bacterial pathogen Xanthomonas campestris pv. campestris (Xcc), which causes black rot disease in cabbage
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Postdoc in Extracellular Vesicles as Mediators of Gut-Microbiome Interactions in Parkinson's Disease
microbiome function in health and disease. We focus on the small intestine (ileum) and colon, using access to ileostomy samples, Parkinson’s disease cohorts, and novel hydrogel/motility models. This approach
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crop breeding by design. You will build models, analyse new sequencing data and optimise strategies for combining multiple advantageous traits. Contribute to groundbreaking research shaping the future
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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