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cause GICs that affect power distribution lines. We will also develop improved methods for estimating the ionospheric currents from ground-based measurements. The ’Solar-Terrestrial Physics and Space
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applied methodologies in Data and Image Analysis, Computational Imaging, Statistical Learning, Uncertainty Quantification, Robust Estimation, and Deep Neural Networks. The group combines expertise in
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PhD Scholarship PhD Opportunity for electrical, telecommunications or computer engineers interested in applying their knowledge to advance quantum communications. The successful candidate will
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these techniques, X-ray fluorescence (XRF) imaging provides detailed information on the distribution of chemical elements across paint layers, giving unique access to pigments, mixtures, and underlying compositions
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Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition; and (iv) Distributed Systems and Networking. These key research areas have a special thematic focus on (a
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systems Experience in deep learning, computer vision, or multimodal data integration Exposure to federated learning, privacy preserving analytics, or distributed systems Knowledge of clinical data models
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considered for Research Assistant. Strong programming expertise in Python and C++, with experience developing real-time robotic and AI systems. Experience in deep learning and computer vision, including
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levels are constrained by a biogeochemical model (POLCOMS-ERSEM, Butenschön et al., 2016), whilst the benthos, cephalopods and fish are represented using species distribution models (Ben Rais Lasram et al
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introduces cell-free (CF) solutions based on O-RAN and AI to improve radio capacity while reducing energy consumption by up to 30% and cutting costs by a factor of 4 via distributed cascaded optical-hybrid
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, especially in the categories of red meat and dairy products, which are among the most emission-intensive commodities. The main objective is to estimate the marginal willingness to pay (WTP) for low-emission