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Field
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applicant will also bring significant experience with general software engineering, with working experience with Cloud Platforms (Google Cloud Platform, AWS, Azure), alongside a strong understanding of recent
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Type Staff Job Description Major/Essential Duties of Job: 1. Develop machine learning or physical based models for plant water stress quantification. 2. Develop machine learning models for crop mapping
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-France F-91440, France [map ] Subject Area: Theoretical Physics / Mathematical physics Appl Deadline: 2025/11/30 11:59PM (posted 2025/10/21, listed until 2025/12/31) Position Description: Apply Position
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subject to continuing based on the availability of funding. The work will focus on the production of large polarimetric maps from the SOFIA data. The position is planned for two years, with a possible
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Instituto de Ciencias Matemáticas (ICMAT), Direction Position ID: 2565-ICMATPDGEOMETRY [#27390] Position Title: Position Type: Postdoctoral Position Location: Madrid, Madrid 28001, Spain [map
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Institut des Hautes Études Scientifiques Position ID: IHES-ERC_GRAVITAS [#30909] Position Title: Position Type: Postdoctoral Position Location: Bures-sur-Yvette, Ile-de-France F-91440, France [map
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KU Leuven, Department of Mathematics Position ID: 1478-POSTDOC [#27272] Position Title: Position Type: Postdoctoral Position Location: Leuven, Vlaams-Brabant, Belgium [map ] Subject Area: Pure
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large remote sensing datasets (e.g., Landsat, Sentinel-2, MODIS) and spatial datasets (e.g., FACTs, FTEM, field data) both locally with R/Python and via Google Earth Engine for wild-treatment outcome
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to enable downstream APIs and feature services Develop ETL workflows for cross-domain spatial data integration using staged refinement (e.g. Medallion Architecture) Engage with UF faculty leading FLDT
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developing LLM-based applications using Python APIs. Experience with large scale molecular dynamics (MD) packages e.g. lammps Experience with version control (e.g., Git) and collaborative software development