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Field
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://as.nyu.edu/biology/directory.fei-li.html This position is for a post-PhD trainee preparing for a research scientist career path. The planned position will provide a transition to career independence through
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master's degree (or equivalent) and PhD in Mathematics/Statistics/Data Science Research expertise in the analysis of complex systems Familiar with network analysis, concepts of resilience (e.g. adaptive
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with partners across Europe: data sharing, code exchange, joint publications and reporting. Your qualities You hold a PhD (or near completion) in Soil Science, Environmental Modelling, Biogeochemistry
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data to develop predictive models. Experiences within numerical modelling of coastal processes is considered an asset but is not mandatory. You are able to work independently and systematically, and you
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Preparation of results for publishing and presentation at conferences Development of models for health and environmental impact assessment Your profile We are looking for a candidate with: PhD in the area of
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experiments (both in the lab and in the field), coordinating cross-cultural studies involving multiple international research groups, data analysis, computational modeling, and writing scientific articles
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31st August 2025 Languages English English English Vacant Post doc position 2 years PostDoc in ocean biochemical modelling Apply for this job See advertisement About NORCE NORCE is a forward-looking
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
. The project is aimed to improve our in-house developed process-based computer model and use it to represent the soil ecohydrological and biogeochemical interactions across various carbon and nitrogen soil pools
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stimulationDURATION: 18 months (potential extension)LOCATION: Université de Montpellier – LMGC, in collaboration with LIRMM, IRMB, and the industrial partner SymétrieSTART DATE: End 2025---POSITION OVERVIEWThe funded
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling