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for Environmental Changes, Academia Sinica Join Taiwan’s top earth system climate modeling team The Research Center for Environmental Changes, Academia Sinica (Taiwan), seeks a Full Research Fellow (professor
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also considered an advantage if the applicant has: Experience in analysing environmental contaminants. Experience in exposure modelling and statistical analysis of environmental data. Experience in
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Environmental Health in French West Indies: Research Chair in Modelling, Clinical or Population-Base
for Environmental and Occupational Health (UMR_S INSERM 1085) is a joint research unit of the INSERM institute (https://www.inserm.fr/en/home/), the University of Rennes (https://www.univ-rennes.fr/en), and the EHESP
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also considered an advantage if the applicant has: Experience in analysing environmental contaminants. Experience in exposure modelling and statistical analysis of environmental data. Experience in
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at the metropolitan scale • Integration of AI-based learning capabilities to refine all types of models studied • Consideration of environmental aspects in the comparative evaluation (positive impact and modal switch
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and human activities. CESBIO scientists make extensive use of remote sensing technologies to monitor environmental changes across spatial and temporal scales and to develop models that address key
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of land management and environmental factors on land carbon and climate dynamics. Tasks and Responsibilities Develop and apply a first-order, spatially explicit model of the biophysical effects of land use
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Research Institute for Environmental and Occupational Health (IRSET - UMR_S INSERM 1085) | Saint Point, Bourgogne | France | about 17 hours ago
://www.irset.org/en ), the Research Institute for Environmental and Occupational Health (UMR_S INSERM 1085) is a joint research unit of the INSERM institute (https://www.inserm.fr/en/home/ ), the University
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Da Costa Sousa (ist12897) Organic Unit: Centre for Studies in Innovation, Technology and Development Policies Scholarship Theme: Modelling of the characterization of the building stock for analysis
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Ph.D. in a relevant field, such as machine learning, climate science, environmental sciences, geoinformatics, or a related discipline. Proficiency in advanced learning techniques and statistical modeling