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, which combines tools from probability, statistics, PDEs, and extreme-value theory to address climate-related questions. Qualifications: Completed PhD degree in Mathematics, with a solid background in at
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developing more complex coupling schemes. The aim is to improve the prediction of natural resources in sedimentary basins. The PhD must have been awarded no more than three years before the start of
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
-Negative Matrix Factorization will be explored. The second challenge is to leverage the derived statistical models to design automated data-driven procedures for the estimation of epidemiological indicators
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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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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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analyses based on statistical methods consider two measurement occasions. Yet, changes of self-reported outcomes over time are often assessed over multiple time points. In this context, the trajectory
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ExperienceNone Additional Information Eligibility criteria Profile: PhD in biology, neurobiology, microbiology or a related discipline. Previous experience in animal experimentation is essential. Experience in
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LevelPhD or equivalent Research FieldAgricultural sciences » AgronomicsEducation LevelPhD or equivalent Skills/Qualifications PhD required, good knowledge of data analysis methos, statistical analysis, QGIS
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sciences » Cognitive scienceYears of Research Experience1 - 4 Research FieldPsychological sciences » PsychologyYears of Research Experience1 - 4 Additional Information Eligibility criteria - PhD in
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, postdoctoral researcher at ALCESTE) and Pauline Georges (PhD student in ground motion attenuation modelling in both projects). The postdoctoral researcher will regularly participate in team meetings, present his