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biomedicine and health. It provides foundations and advances in quantum information sciences to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and
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Requisition Id 16779 Overview: We are accepting applications for Postdoctoral Research Associate positions in Data Science for Advanced Manufacturing that will focus on the development of next
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data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly
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, Python or R Experience in manipulating and analyzing large observation data or model outputs Working knowledge of terrestrial biogeochemistry and nutrient-cycling processes Strong communication skills
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, Python or R Experience in manipulating and analyzing large observation data or model outputs Working knowledge of terrestrial biogeochemistry and nutrient-cycling processes Strong communication skills
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, root imaging) with biogeochemical, microbial, or environmental sensor data. Experience analyzing large datasets in reproducible formats (R, etc.) Demonstrated interdisciplinary and systems-level approach
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time-of-flight secondary ion mass spectrometry (ToF-SIMS), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Experience in data reduction of big spectroscopy, mass spectrometry, and image
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of large-scale geospatial and time-series datasets. The candidate will develop and evaluate multimodal AI models to characterize vegetation and land-surface dynamics and quantify ecosystem responses and
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will design and implement differential privacy solutions for large-scale scientific data models in federated learning environments. You will advance privacy-preserving machine learning by developing