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Field
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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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oxides, we will first develop and benchmark machine-learning interaction potentials of increasing complexity. Subsequently, we will deploy a combination of brute-force and rare-event sampling to isolate
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take place at ICSN (http://www.icsn.cnrs-gif.fr ), a CNRS (French National Centre for Scientific Research) research unit specializing in chemistry and biology, and part of the Université Paris-Saclay
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. Unsupervised machine learning approaches will be used to identifiy key dimensions of circadian rhythm associated with dementia subtypes. This requires a very good level in statistics and R programing as
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. Proficiency in programming and data analysis. Experience in imaging/microscopy is an asset. Autonomy, rigor, creativity, team spirit, and strong communication skills. Additional Information Selection process
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The project aims at developing new learning methods
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Website https://emploi.cnrs.fr/Offres/CDD/UMR5277-SANCHU-090/Default.aspx Requirements Research FieldAstronomyEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldAstronomyYears
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for both projects. The work will take place at IRAP with Drs JF Donati and C Moutou, starting Q4 2026 (preferably) or Q1 2027. IRAP, PS2E stellar physics / exoplanet group Where to apply Website https
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- Quantum Electronic Circuits Alps. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UPR2940-ELOBER-173/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent Research
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to apply Website https://emploi.cnrs.fr/Offres/CDD/UPR3228-SEVBOR-002/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD