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agencies. The objective is to share and collaborate with international expertise to achieve excellence in space. Key Job Purpose: We are looking for a Research Fellow to work on data assimilation system
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methods in meteorology (atmospheric data assimilation). This contributes to the cutting-edge research expertise of the College and the University in the strategic areas of Machine Learning, Statistical Data
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or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the globe. Candidates with
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climate projections through teleconnections. As a PhD-candidate in GRADIENT, you will join an interdisciplinary team with expertise in climate dynamics, paleoclimate, data assimilation, and climate and
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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modelling - covering empirical, physics-based, and data assimilation techniques - radio propagation, satellite orbit determination, and HF engineering. This 3-year post will provide the candidate with
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one of the following fields: process-based model development, Earth system model simulation and analyses, data assimilation, large-scale data collection and synthesis, high performance computing, and