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/engineering degree in artificial intelligence/computer science/applied mathematics; demonstrated abilities in research or problem solving tasks (public challenges, coding competitions, published research, et
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supervision collaboration in national or international research projects (optional) Requirements: university degree in Computer Science, Computational Linguistics, Mathematics or a related field solid knowledge
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Application Deadline 29 Aug 2026 - 01:06 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Mathematics or in mathematical aspects of Computer science, with excellent results. Start in or around September 2025 ; an earlier or later starting date is possible. The Mathematics department offers
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28 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Computer science Physics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country
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, mathematics, physics, remote sensing and machine learning. Experience and skills · Strong interest in modelling, model-data integration, and remote sensing data analysis. · Knowledge of programming, remote
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, environmental engineering, informatics, and arts. The faculties are located on the main campus (Holländischer Platz) and on other campuses (Faculty of Mathematics and Natural Sciences at Heinrich-Plett-Straße
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contribution to addressing the major societal challenges of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics
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contribution to addressing the major societal challenges of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics
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interannual variability of spectral signatures in different bands (Planet, Sentinel-3, Sentinel-2, ECOSTRESS, Landsat, SMAP), which will be linked to LUE-WUE and gc information from multiple eddy covariance