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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria The position requires a PhD in machine learning, NLP, causality, or a related discipline, with a strong command of deep
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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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Statistical Signal Processing, Data Science, Machine Learning with an interest in astrophysics - or a PhD in Astroparticle Physics with skills and professional experience in experimental data analysis. Website
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the philosophy of science (including philosophy of logic, mathematics, and computer science), as well as about forty PhD students and three research support staff. The IHPST maintains numerous national and
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/simulation programming - characterisation of various samples - supervising student (intership, PhD candidate) - writing articles - taking part in conferences This work will take place at ISMO within
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conceptual DFT (linear response function, Fukui functions) or QTAIM theory (delocalization index), and their validation on a set of compounds known from the literature - interfacing a MLIP (Machine-Learned
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or imitation of these signals affects the fish's responses. In the first year, the team—composed of researchers, engineers, and PhD students—built an experimental arena equipped with high-speed cameras and
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ExperienceNone Additional Information Eligibility criteria The postdoc should have a PhD degree in evolutionary biology, with expertise in bioinformatics, statistics, programming and/or modeling. Previous
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and machine learning applied to data fusion and adapt them to the field of exoplanet characterization. They will develop and maintain the FORMOSA code in coordination with the team of students working
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are looking for a postdoctoral researcher in the field of image generation algorithms (specializing in Deep Learning) for a 12-month position. The work will take place within the IMAGE research team