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key elements to answer the question of the causes of changes in ozone trends throughout the troposphere. This will involve exploring regional and vertical differences to better understand the dominant
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experiment on a metric-scale concrete wall, using the multi-physics NDE probe integrated onto drone platforms. Expected Results A Python-based multi-physics Maching Learning framework for NDE characterization
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objective of the thesis is to model the intermolecular interactions between metabolites and a chemically modified gold surface in the presence of different ions. Molecular modeling will be performed with
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-carrier (SC) techniques described in [3], the narrowband beamforming model, where signals received over different antenna elements are identical up to a phase shift, may become invalid so that additional
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to 1D stress-strain paths allowing for injection of non-wetting fluid to test the effect of calcite dissolution on breakthrough. Samples for the oedometric test will be prepared with different pore-fluid
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-chemical properties similar to conventional kerosene, their combustion behavior can differ significantly, requiring adjustments and optimization of current gas turbines (GT). In this context, numerical
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.: +33 (0)4 76 88 22 80, email: schulli@esrf.fr ), Expected profile A background in X-ray diffraction or electronics would be desirable and knowledge of programming (Python) would be an advantage. Teamwork
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of command-line tools, Python, or R for data analysis is a significant advantage. Language: Proficiency in English (written and spoken) is mandatory, as this is an international collaboration project. French
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or equivalent) in physics A background in solid state physics is highly recommended Aptitudes in programming (Python) are a plus Proficiency in English (working language at the ESRF) Working conditions Your shall
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primarily target data scientists. In fact, much of these available technologies presuppose technical expertise comparable to that of professional programmers, including skill fully employing different low