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. The objective of this thesis project is to develop hybrid models that integrate electrochemical principles with machine learning techniques to analyze data from electrolyzers, predict performance, assess lifespan
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. This PhD project aims to achieve three main objectives: (i) Identify, using empirical data, the determinants of floral induction and flowering effort; (ii) Develop an evolutionary model of masting based
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of the landscape over time. The LANDIS-II forest landscape disturbance and succession model will be used to perform simulations based on palaeoecological data. The student will collaborate with project researchers
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source of information for the next IPCC Assessment Report (AR7). The proposed PhD is part of this context and will directly support the French contribution, using the Elmer/Ice model, to ISMIP7
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of PhD students and post-docs working on different aspects of seafloor spreading (magmatism, tectonics, hydrothermalism) on a range of time scales, with observational and modeling approaches
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» Control engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France Application Deadline 12 Oct 2025 - 23:59 (Europe/Paris) Type of Contract Temporary Job Status Full
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to animal fungal pathogens and further explore and test the above mentioned characteristics of this model. To achieve this, the PhD student will use the animal fungal pathogen Pseudogymnoascus destructans
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17 Sep 2025 Job Information Organisation/Company Université de Caen Normandie Research Field Physics Chemistry Engineering Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions
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FieldEnvironmental science » Earth scienceYears of Research ExperienceNone Research FieldEnvironmental science » Global changeYears of Research ExperienceNone Additional Information Eligibility criteria - PhD obtained
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modeling. Each PhD will lead to a double degree awarded by two partner universities, preparing graduates to become leaders in Europe’s energy transition. DC7 PhD Position "Uncertainty Quantification