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computing function and training of artificial neuron network have been demonstrated based on single nanomechanical device. The main mission of this postdoc project, financially supported by IMITECH project
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, laboratory meetings, as well as at workshops and conferences covering the various aspects of the thesis: high-performance computing, numerical methods, and computational cosmology. An annual meeting of
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area, such as P. Urbani (IPhT), A. Rosso (LPTMS), C. Furtlehner, S. Chibbaro (LISN). The postdoc will have dedicated funding for conferences and computing equipment. Where to apply Website https
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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the
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codes) to disentangle the relative contributions of radiative and mechanical energy to JWST spectra. Using existing and newly computed model grids, the postdoc will develop an integrated framework to
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committed to reproducible research and to mentoring students. Research Environment and Supervision: The postdoc will be a member of the Astroparticle and Cosmology group at LAPTh, and will be
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algorithmic approaches and be conducted in the context of wireless networks, the Internet of Things (IoT), distributed learning, or edge computing infrastructures. The research topics may include, the
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consumption of microelectronic devices presents a major challenge, accounting for up to 50% of global electricity consumption by 2030. This situation is largely due to the Von Neumann computing
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test and compare the predictions of this new configuration against existing theories (which model these structures in parallel) using synthetic case studies. These numerical tests will aim to clearly
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learning results in restricted formal contexts. The objective of the proposed PostDoc is to work at the intersection of model counting and machine learning, with the aim of significantly improving