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datasets, our research focuses on developing algorithms and computational methods to detect patterns and generate insights. BDA blends a wide range of expertises, including bioinformatics, data mining, data
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develop algorithms for segmentation, motion tracking, elastography, and biomechanical analysis of aneurysms, with the goal of improving patient-specific rupture risk assessment beyond traditional diameter
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‘healthy biodiversity’ into quantifiable impact indicators; Develop a spatial optimization algorithm that finds land use configurations that optimize these indicators; Compute Pareto frontiers under
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stakeholders’ preferences in terms of ‘productive agriculture’ and ‘healthy biodiversity’ into quantifiable impact indicators; Develop a spatial optimization algorithm that finds land use configurations
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the interface between the classical and quantum worlds. You will design QEC codes suited to realistic hardware, develop the decoding algorithms that make them practical, and map the trade-offs between reliability
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for the analysis and integration of –omics data. The group has a strong track record in (integrative) computational omics analysis, algorithm development, machine learning and scientific data infrastructure
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reconfiguration operation. Develop and evaluate fast and efficient scheduling algorithms for fast control and reconfiguration of the optical AI compute clusters. Realize a small-scale compute cluster lab testbed
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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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on this project, you will: develop mathematical theory for non-linear inverse problems governed by wave equations; design and analyse numerical algorithms for inverse problems, uncertainty
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, enabling more efficient downstream metallurgical processing and improved metal circularity. Over recent decades, numerous sensing technologies have been developed for metal scrap characterization. Yet