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adipose tissue. In particular, we will study the role of different membrane receptors and their signaling pathways in the browning process. The various techniques used will include cell biology and genetic
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communication skills in English Ability to work efficiently, both independently as well as in a team Previous experience in the fields of soft matter, metamaterials, quantitative image analysis and programming
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the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors. The LCSB recruits talented scientists from
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: the Center for Nuclear Sciences and Material Sciences (CSNSM), the Laboratory for Imaging and Modeling in Neurobiology and Cancer Research (IMNC), the Orsay Institute of Nuclear Physics (IPNO), the Linear
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contributes to neurodevelopmental disorders (NDDs). Using stem cell culture, imaging, genomic, and epigenomic approaches, the successful candidate will characterize paralogue expression profiles, cellular
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infrastructure managers in developing cross-sectoral strategies to proactively shape infrastructure demand, as an alternative to the traditional and increasingly untenable 'predict-and-provide' paradigm. By
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
at international meetings, workshops and conferences Preferred Qualifications and Skills Experience with AI-based image analysis Trained drone operator Familiarity with ship-based whale survey methods Further
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endoscopy, this is the right research project for you. The PhD research project aims to explore and develop probes for ex-vivo and in-vivo applications for tissue imaging, classification and identification by
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ResTOrES project will develop, test, and demonstrate a prototype resilience assessment toolkit for offshore energy systems. The toolkit will enable the quantification of resilience in terms of appropriate
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual