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eNSEMPLE. It is an interdisciplinary project at the interface between Statistical Physics, Data Science, Network Science, Computer Science and Sociology, and will involve collaborations with researchers from
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observed in optomechanical platforms [2]. Practically, the applicability of modern quantum technologies in optomechanical networks ultimately requires quantum entanglement of light and many vibrations—i.e
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energy materials—and is equipped with state-of-the-art research facilities. Embedded in a dynamic network of industrial and academic collaborations, SIMaP provides an ideal environment for ambitious
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AI researchers from ANITI, IMT and CERFACS, as well as with researchers/engineers in weather forecastings from the CNRM (Météo-France). Hybridization methods between neural networks and physical models
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The expert will participate in the necessary methodological developments and analyses of airborne data recorded by the IAGOS research infrastructure (https://www.iagos.org ) and from other networks, to provide
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• Participation in the international Long-Term Ecological Research network or a similar ecological research network • Experience working with spore-forming Firmicutes (bacilli) and/or Actinomycetes (culture
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Starrydata2). The work will include the implementation of machine learning models (neural networks, random forests, SISSO), generative approaches for predicting crystal structures, the use of machine learning
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different methods of analysis used in the community, in particular linguistic probes (classifiers trained to predict certain linguistic properties from representations discovered by neural networks
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, Interactive and Cognitive Systems, Distributed Systems, Parallel Computing, and Networks. The host team, DAISY, is a joint CNRS, Grenoble INP, and UGA research team handling research challenges
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are being envisaged for future 6G networks [1,2] as a first line of defense with low latency and low computational cost. A key requirement for their practical implementation is the guarantee of an asymmetry