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under the guidance of Prof. Ivan Nourdin. Your role Conduct research in machine learning, deep learning, and probabilistic modeling, with a focus on real-world applications Disseminate research findings
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of mechanical forces within the neuroepithelium of the embryonic spinal cord, using organoid models derived from human induced pluripotent stem cells. iPSC cell culture CRISPR-Cas Imaging Image analysis
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, electrical, and thermal properties, and the production process (conventional and solar). • To accurately model and optimize the nano and macro structure of the graphenic carbon-metal system in relation with
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digital models, technologies and solutions for a society and economy that respect people and their environment. We are looking for a postdoctoral researcher in AI applied to RF dosimetry, to contribute
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familiarity with ultrafast optics. The successful candidate will join the Nanomagnetism and Modeling Team at the Institut des Molécules et Matériaux du Mans (IMMM).
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preclinical models. Addiction-like behaviours and related striatal neuromodulation will be investigated through the combination of intravenous cocaine self-administration (SA) and fiber photometry in transgenic
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, meetings, reports) Writing scientific articles Contribution to microwave modelling of ice and snow cover emission Travel to meetings with the European Space Agency (ESA), to maintain collaboration with
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Postdoctoral position: Developing a human lymphoid organ-on-chip to evaluate candidate mRNA vaccines
A post-doctoral position is available to develop a 3D model of a human lymph node and apply this model to preclinical vaccine evaluation. The successful applicant will join the team of Lisa
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to conduct proof-of-principle research and characterize NPC pathway components in mouse models in the context of neurological disorders and cancer. How to apply: Applicants should hold a PhD in biology
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Keywords Optogenetics, 2-photon activation, large scale electrophysiological recordings, mouse model Lab description Processing of auditory information in the brain is complex because information