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Università degli Studi di Padova - Dipartimento di Biomedicina Comparata e Alimentazione | Italy | 10 days ago
crab.Extension of the above described hydrodynamic and environmental characterizations into the near future to identify potential changes related to climate change.Production and provision of modelling outputs
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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for the mitigation of air pollution and climate change. This research supports the activities of the Climate and Clean Air Coalition (CCAC http://www.ccacoalition.org ), the World Economic Forum and the Clean Air
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on project findings and work to engage, get feedback on and promote the use of the Pro-Climate computer model as an aid to land use planning activities. The first case/living lab is work to promote awareness
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modeling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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plankton communities and impacts of climate change on marine environments. THE DEPARTMENT The department of Ocean Systems (OCS) studies the role of the ocean in a changing climate, from the equator
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therefore collaborate with colleagues in climate science, systems modelling, and policy analysis. Where to apply Website https://www.academictransfer.com/en/jobs/356362/phd-integrated-assessment-model
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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
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between climate dynamics and marine biogeochemistry is also essential. The successful candidate will demonstrate proficiency in numerical modeling and statistical methodologies for interpreting in-situ and
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a group of species. Data on their distribution in these territories will be updated and forecast models of their future distribution will be developed, taking into account possible climate change