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laboratory techniques (mammalian and bacterial) Multi-omics data analysis CLSM and SEM imaging skills Strong analytical, problem-solving skills and Excellent written and verbal communication skills and ability
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establishments (Université Côte d'Azur, CNRS, INRAE, INSERM ...), but also with the regiona economic players. With a presence in the fields of computational neuroscience and biology, data science and modeling
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an excellent reputation in its field with state-of-the-art facilities and leading scientists in the areas of biocatalysis, enzymology, organic chemistry and molecular imaging. Our biocatalysis community has a
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: Statistical signal/image processing, deep learning, machine learning, neuromorphic computing Good communication skills and an appropriate publication record are essential. Solid knowledge of Python and C++ is
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at the Humanitas University campus. Their common mission is advancing science to make a difference in patients' life. Humanitas Research is guided by unmet clinical needs and it leverages high-end technologies
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uncover how epithelial cells organise in space and time under different physico-chemical environments to drive self-organisation processes, like condensates, that shape mesoscale structures enabling tissue
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on identifying the brain regions associated with different cognitive processes, but more recent studies seek to understand the nature of the information stored in various brain regions, or representations, and how
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Vision Group at the division of Signal processing and Biomedical Engineering develops intelligent systems for automatic image interpretation and perceptual scene understanding. Our research spans both
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Engineering, Science and Theory (NESTiD) Scientific Computing (SciComp) Vision, Imaging and Visualisation (VIViD) We are ranked 4th in the UK in the Complete University Guide 2024. For more information, please visit our
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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence