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campus. We are particularly interested in researchers working in mathematical artificial intelligence, broadly construed. This includes, but is not limited to: machine learning algorithms, formal proof
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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learning, physical AI, and spatial AI. The RA will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Project Officer to assist
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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satellite constellations [2]. This PhD aims to develop a comprehensive analytical and algorithmic framework for deterministic QoS guarantees in dynamic LEO satellite constellations. The research will pursue
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error-correcting codes, establishing fundamental performance limits, and building practical decoding algorithms and architectures. Your research will sit at the interface between the classical and quantum
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data) will help validate observations and refine predictive models. Automated monitoring tools (scripts, dashboards, alerts) incorporating machine learning algorithms or statistical methods will be
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Researcher position. The selected candidate will work on research and development for testing, analysis, and integration of AI and machine learning (ML) algorithms in new simulation and training architectures
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involving Prof. Dr. Michael Bader (TUM CIT, Hardware-aware algorithms for HPC) , Prof. Dr. Felix Dietrich (TUM CIT, Physics-enhanced Machine Learning) , and Prof. Dr. Hartwig Anzt (TUM CIT, Computational