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other process modeling tools. https://agilebiofoundry.org/ https://bioesep.org/ The successful candidate will be able to: • assimilate a wide variety of information into assessments • contribute
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ice sheet surface data assimilation: Employing satellite observation and machine leaning to improve model representation of ice sheet surface melt'. The candidate will work under the direction of Prof
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7 Mar 2025 Job Information Organisation/Company Foundation for Research and Technology-Hellas Department Institute of Molecular Biology and Biotechnology Research Field Biological sciences
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the project/s as needed based on statistical analyses. Expectations: Read literature articles, develop new ideas, and assimilate the information into project design/interpretation. Assist in writing research
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ | Potsdam, Brandenburg | Germany | 3 months ago
a related field Advanced expertise in spatial data analysis, assimilation methods for Earth science applications Expertise in the field of glaciology and glaciological modelling Demonstrated expertise
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Your qualifications: Master's degree (or equivalent) and PhD in hydrology, cryosphere, glaciology, data sciences, or in a related field Advanced expertise in spatial data analysis, assimilation methods
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Detail Information Position Summary As a Postdoctoral Associate in the Department of Earth Sciences , this position will support an investigation entitled “Toward ice sheet surface data assimilation
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14 Mar 2025 Job Information Organisation/Company National Centre for Nuclear Research Department MAB NOMATEN Research Field Physics » Other Engineering » Materials engineering Researcher Profile
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& data assimilation and / or incorporation of tracers into hydrological models would be advantageous. Access to high-performance computer clusters is available to facilitate use and development of “state