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physically consistent and to enforce desired structure in the results. The second is physics-informed learning, which combines available historical data with known system dynamics as a regulariser
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provide interpretable descriptions of biological processes, but they are often incomplete: mechanisms may be only partly known, data are noisy and sparsely sampled, measurements vary across individuals
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data‑driven differential rotation constraints in the global dynamo models (e.g., via relaxation terms in the Navier–Stokes equation), calibrating against solar/stellar observations. Design, run, and
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Fingrid. Research focus Monitoring and data analysis: Apply and develop methods to estimate torsional oscillation frequencies, damping and amplitudes from phasor measurement unit (PMU) data. Analyse
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Planning and running the in-situ uplift experiments and cyclic liner tests Building the measurement chain from displacement sensors, pressure measurement, data acquisition to running the supporting
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Marie Skłodowska-Curie Doctoral Network, runs from 2026 to 2030, and trains 15 Doctoral Candidates (PhD students). The DN targets developing software-defined technologies that turn edge data centers
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Advanced energy solutions. Topics extend from fundamental research to important applications. We educate future generations of research and development professionals, data specialists, technology experts
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development led by E-Sailor 15. The research includes conducting laboratory and in-orbit experiments using data from the Foresail-1p mission, analysing tether dynamics, imaging, and operational behaviour. Based
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Similar jobs Research Engineer in the Center for Interdisciplinary Data Science and Artificial Intelligence Abu Dhabi, United Arab Emirates Post-Doctoral Associate in the Center for Interdisciplinary
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authenticity of generated and watermarked audio data, improving content-based audio watermarking, and evaluating robustness against removal, spoofing, adversarial attacks, and realistic downstream processing