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Translational Biophotonics Laboratory (A*STAR Skin Research Labs, Singapore), we are developing novel biosensing probes based on (specially designed) optofluidic fibers associated with plasmonic nanotechnologies
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analyses, isotope-based approaches (CSIA), and molecular biology tools to investigate: • contaminant fluxes and bioavailable fractions in urban aquatic systems, • transformation processes and interactions
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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interoperable motif-based software components (libraries, frameworks, tools) that can be easily deployed and instantiated in the various CSE application environments. This is addressed iteratively through
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learning simulations - Growth of metallic heterostructures by sputtering / ALD - Optical and e-beam lithography - Ion beam and reactive etching - Fabrication of skyrmion based nano-devices - Electrical
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This postdoctoral contract is based on the Emergence
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Description Within the ANR HEBBIAN contract, the objective is to adapt bio-inspired Hebbian learning models recently proposed by one of the partners of this ANR (Frédéric Lavigne) in order to account for data
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elucidating the molecular and cellular mechanisms of the late phase of long-term potentiation (LTP), a key process in learning and memory. The project is based on the development and use of an innovative
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the collected data qualitatively and quantitatively - Write scientific articles based on the research conducted Recruitment is handled by the CLLE Laboratory (Cognition, Languages, Language, Ergonomics; CNRS