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Information Eligibility criteria - PhD in theoretical chemistry applied to materials, materials physics, or computer science/applied mathematics; - Solid experience in DFT applied to periodic systems (codes
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- 4 Research FieldPsychological sciences » PsychologyYears of Research Experience1 - 4 Additional Information Eligibility criteria - PhD in cognitive neuroscience or cognitive psychology - Experience in
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, - A set of environmental data associated with surface (0-200m) PSDs and concentrations The post is for 12 months, with a start date around January 2026. - Assemble datasets in a format ready for
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Research FieldPhysicsYears of Research Experience1 - 4 Additional Information Eligibility criteria The successful applicant must have completed a PhD in Particle Physics. Acquaintance with flavour physics is
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of Research Experience1 - 4 Research FieldPhysicsYears of Research Experience1 - 4 Additional Information Eligibility criteria - PhD in physical chemistry or materials science with skills in electrochemistry
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ExperienceNone Research FieldHistory » History of scienceYears of Research ExperienceNone Additional Information Eligibility criteria • PhD in Applied Mathematics, Data Science, or Statistics • Expertise in
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LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria Candidates must have a PhD in theoretical physics, preferably in soft matter physics. They should be
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FieldComputer scienceYears of Research ExperienceNone Research FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria The candidate must hold a PhD in computer science (or a
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- Participation in the supervision of internships and PhD theses This postdoctoral position is part of the ANR project Imagique, in collaboration with laboratories in Grenoble and Saclay. The successful candidate
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Additional Information Eligibility criteria The candidate should have a PhD in Biology/Evolutionary Biology and skills in bioinformatics and macroevolution (ideally models of phenotypic evolution