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data from December 2025 to the present to identify workload distribution patterns and refine the algorithm using mathematical modeling, programming, and integrated data systems. Project outcomes will
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learning, large-scale model optimization, and generalization. To explore scalable optimization methods for large-scale, distributed, and multi-node collaborative training. To conduct theoretical analysis
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identification through lab-scale and field experiments. Key Responsibilities: Develop algorithms for guided-wave analysis, response analysis, sensor fusion, and system identification using distributed and multi
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/cee. We are looking for a Research Fellow, Distributed Acoustic Sensing to advance research on distributed fiber-optic sensing for infrastructure, urban, and environmental applications. The role will
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/cee. We are looking for a Research Fellow, Urban Geophysics and Seismic Noise Monitoring to conduct research in urban and environmental geophysics using distributed acoustic sensing on pre-existing
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of algorithms for medical image analysis. The successful candidate will investigate computational complexity, stability, and numerical summaries of multiparameter persistence, as well as applications to medical
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applications to medical data. The project will combine theoretical work on multiparameter persistence with the design and implementation of algorithms for medical image analysis. The successful candidate will
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algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing extreme-scale scientific data management
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electromagnetic and thermal simulations. This work will include detailed tissue segmentation from medical images, integration of automatic and semi-automatic segmentation algorithms, refinement of anatomical
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, physical AI, and spatial AI. The RF will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision Group’s long