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, you must have a PhD in a relevant field. As a suitable candidate, you have expertise in deep convective cloud processes and experience with scientific data analysis. Prior experience in applying machine
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible
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Infrastructure Engineering. Undergraduate and graduate degrees (Master and PhD) are offered in civil & environmental engineering, computer engineering, electrical and electronic engineering, and mechanical
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. theses at the interface between structural engineering and machine learning. You will disseminate your research through peer-review publications and participation in international conferences. You will
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experience and enhanced potential to receive an ERC Starting Grant in the future. Open to both PhD (natural sciences) and MD (medical sciences) holders. From a variety of academic backgrounds: molecular
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of climate model output by means of classical statistical and machine-learning methods #coordination of scientific workflows among project partners Your profile #Master's degree and PhD degree in meteorology
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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Postdoctoral researcher (f_m_x) - Waves in the Inner-magnetosphere and their Effects on Radiation...
of the adverse effects of the space environment utilizing satellite observations, physics-based numerical models, machine learning, and data assimilation. Our research will help safely design and operate
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observations, and remote sensing data to assess the impact of global change on ecosystem productivity and sustainability. You will develop novel algorithms to integrate data-driven machine learning and process