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multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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neural networks under symmetry constraints, their optimization dynamics, and their generalization behavior—particularly in low-data or out-of-distribution settings. The work combines formal theoretical
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with neuroimaging, numerical mathematics, optimization, inverse problems, software development, motivation and research interests. The location for this research will be the workgroup of Prof. Dr
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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
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to numerous preclinical research projects focused on the development of novel molecular magnetic resonance imaging (MRI)-based techniques for early detection, disease phenotyping and monitoring treatment
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scientists with numerous international collaborations and partnerships and have funding from the National Institutes of Health and the Canadian Institutes of Health Research. This position will join a diverse
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 25 days ago
professionalism, enhance learning, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our