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existing structural and functional MRI data, acquire new data in collaboration with clinical researchers, and prepare publications and conference presentations. - Study preparation - Data acquisition (MRI
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industrial partners. - Construction of electrochemical cells incorporating specially designed magnetic field sources, including quantitative measurement of local magnetic fields. - Implementation of tools
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together expertise in physics, chemistry, nanoscience, and materials engineering. For more information about IS2M, please feel free to visit the website: https://www.is2m.uha.fr/ . The PhD candidate (M/F
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to structured programming in C++ and Python - knowledge of linux / unix operating system - fluent knowledge of spoken and written English - fundamental knowlegde of machine learning (and statistics) - good level
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structural data, which requires laboratory based as well as on-site analyses. The main objectives are as follows: Compile legacy data of stained glass windows, this requires extensive data curation and
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on annotated structures, which could eventually lead to automated comparative grammars. The mission is funded by the ANR Autogramm research project (https://autogramm.github.io/ ). Autogramm focuses on exploring
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structural changes in synapses to transcriptomic regulation Promote scientific results through publications and scientific communications Experimental activities Performing patch-clamp electrophysiological
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physics, and mathematical physics. The cosmology and astroparticle team (https://astrocosmolapth.com ) conducts research on cosmic large-scale structure, cosmic microwave and infrared backgrounds, cross
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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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. Argument(ation) mining, the new and rapidly growing area of Natural Language Processing (NLP) and computational models of argument, aims at the automatic recognition of argument structures in large resources