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The postdoctoral researcher will join the "Network Dynamics & Computations" team led by Srdjan Ostojic and develop research projects on modeling neural circuits and their role in behavior. The work will focus
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). The unit is divided into ten research teams of varying size covering the thematic axes of photonics and waves, materials, energy, reliability of systems in constrained environments and sensors and
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concerning the information sciences and technologies of the future in the fields of the environment (photovoltaics and sensors for the nuclear industry). health (interaction between waves and living organisms
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sensors dedicated to the mid-infrared. This work is funded by several ongoing ANR projects within the research team. This position may be renewed once for an additional period of between 18 and 24 months
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porous solids for the capture and/or degradation of toxic agents (or simulants) and sensors. Main activities Identification of MOFS composition Using existing databases that have already identified
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implement and train neural network architectures, including Physics-Informed Neural Networks (PINNs), in order to integrate physical constraints into the learning process and improve the identification and
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-informed neural networks (PINNs) and potentially generative adversarial networks (Pi-GANs). These models aim to predict cell fate and tumor development in CRC. The postdoc will collaborate with both
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source and made available to researchers, for example to calibrate the hyperparameters of a neural network. Definition of research activities and tasks to be accomplished: To meet these challenges, we
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, which in turn will be used to engineer highly specialized neuronal cellular subtypes for cell transplantation therapies. To achieve this goal, the candidate will combine a gene network-based approach with
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome