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belongs to one of the three marine stations of Sorbonne Université. With about 120 permanent staff, the LOV generates and analyses a large quantity of marine data, including imaging, genomic, and satellite
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 10 days ago
latent spaces). Integrate dynamic, geometric, and biophysical features extracted from large MD simulations. Train and benchmark models on state-of-the-art datasets. Collaborate with PhD and Master students
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integrate the use of Large Language Models (LLMs), LLM agent, Agentic AI models and automated reasoning approaches for the interpretation of complex data, the analysis of experimental protocols, and the
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. Activities The postdoctoral researcher will be part of a team involved in the data analysis and interpretation of two major very-high-energy gamma-ray observatories: the Large High-Altitude Air Shower Array
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semiconductor heterostructures • Perform quantum measurements at low temperature • Cosupervise PhD students on related project • Communicate results Institut Néel, is a large laboratory covering many different
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applied mathematics, physics, computer sciences or social sciences with outstanding skills in quantitative methods ; - Provable experience working with social media data, specially very large datasets (we
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their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps. The project emphasizes spectroscopic galaxy surveys—in particular
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of propagations of high-energy particles through magnetized medium and analysis of data of different gamma-ray telescopes: Fermi Large Area Telescope, Cherenkov Telescope Array Observatory (CTAO), Large High
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LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Prerequisites: PhD in applied mathematics or physics with a strong theoretical component Strong
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. Automated data-driven selection procedures will enable to gain objectivity and capacity to handle large amount of data from a wide range of epidemics. The first challenge consist in refining previous models