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metabolomics. Our studies focus on developing new mass spectral data analysis algorithms (e.g., clustering) to better solve the common key persistent problems arising from factors such as mass shift and peak
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national and international reference point in quantum technology research. The integrated approach—which combines experimental development, numerical simulations, and advanced algorithm design—will create a
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, economics, and all branches of science. Current concerns include the development and analysis of algorithms for the solution of problems of estimation, simulation and control of complex systems, and their
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, secure, scalable, and human-centered mission capabilities prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities identify and investigate
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microscopy is often limited by slow acquisition speeds and large volumes of redundant data, restricting its applicability in real-world scenarios. The goal of this PhD project is to develop a snapshot spatio
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new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities. This role involves research and
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inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real-world datasets. The core responsibility is to build and validate federated causal inference
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learning based optimization algorithms, human and AI coordination in best decision making for urban transportation related problems. The role will focus on developing generic frameworks and innovative
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-driven, machine learning approaches. The biomass data product will be validated by data from an international network of ground-truth forest sites (GEO-TREES, geo-trees.org). The developed algorithms thus
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systems that are both scalable and explainable. This role bridges algorithmic research and systems implementation, offering opportunities to collaborate with leading academics and engineers on developing