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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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tend to be static, ambiguous, and insufficiently contextualised to complex and fast-changing environments. In this project, we develop two research lines. The first investigates the opportunities and
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of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In
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psycholinguistics, brain-computer interfaces, robotics, cognitive modeling of language, computational linguistics, educational technologies, computational modeling of evolutionary and adaptive systems, image and
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tend to be static, ambiguous, and insufficiently contextualised to complex and fast-changing environments. In this project, we develop two research lines. The first investigates the opportunities and
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, RNA biology, organoid models, and the tissue microenvironment to tackle biomedical challenges with translational potential. The postdoctoral position is part of a collaborative project between the
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physics-based theory with data-driven models, you will contribute to the next generation of predictive tools for materials design and discovery. You will also collaborate closely with experimental and
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learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In this role, you will
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Postdoctoral Researcher in Gravitational Wave Astroparticle Physics (GRAPPA, University of Amsterdam
Bertone? GRAPPA is looking for an ambitious Postdoctoral researcher. The successful candidate will help advance theory and computational modelling of compact binaries in astrophysical/dark matter
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applications from individuals with experience in: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques