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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
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been proposed: traditional computer‑algebra methods [3], reduction of the problem modulo a prime p [6, 2], and symbolic‑numeric methods [4, 1]. This postdoc proposal concerns the second modular approach
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, electron microscopy, X-ray diffraction, etc.). Methodology: • Design and synthesize model substrates to measure the activity of enzyme mimics. • Develop analytical methods to detect and quantify chemical
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://igdr.univ-rennes.fr/ team-mitochondrial-biology-and-integration-with-the-cell-cycle) focuses on state-of-the-art methods and tools in quantitative fluorescence microscopy to study the spatiotemporal
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difference operators, our focus will be on a Fourier-space description of spatially periodic velocity fields, taking direct inspiration from Fourier pseudo-spectral methods used in standard DNS codes
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong
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, optimal transport, set evolution and shape optimization, calculus of variations), and/or convex/non-convex optimization methods (first-order algorithms, nonlinear/non-Euclidean gradient descents
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groups attempt to influence criminal policies through the European human rights judicial systems by elaborating and applying judicial, political, and financial strategies. Through a legal method
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of statistics is preferred. Experience with experimental work and molecular ecology methods is an asset. The candidate must demonstrate proven ability in independent scientific research and skills in writing
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journal. • Organize a conference. LISIS is a joint research unit of CNRS, INRAE, and Gustave Eiffel University. Its members mobilize the methods, concepts, and perspectives of the social sciences needed