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of the content and profile of bioactive compounds, amino acids, and antinutritional components in plant matrices (legumes and pseudo-cereals); - Development and optimization of different biotechnological processes
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hardware technologies. Conduct hardware performance evaluations (e.g. area, power, efficiency). Develop software strategies for communication-aware task scheduling and runtime optimization. Explore low-power
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collection, and applied mathematics. Our goal is to make optimal use of past climatic information to better understand Earth’s climate response to various kinds of forcing, focusing on abrupt climate
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structured around two main pillars: Network resilience and sovereignty, i.e., research on networking architectures and mechanisms that keep critical networks and applications they support running optimally
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integral equations Machine learning, especially the areas of optimization, learning theory, probabilistic modeling, deep learning, and high dimensional data analysis, as well as applications of scientific
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for an ultra-high vacuum synchrotron end-station using CAD software. - Run, optimize, and document data acquisition codes (LabVIEW and Python) - Aid NIST staff in developing plans
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for teamwork, problem-solving, and collaborative relationships Strong technical background in at least one of the following areas: Mathematical optimization, Resource allocation, Machine learning, Wireless
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in yeast cultures. Workplan and objectives to be achieved: Optimization of bioprocesses to produce yeast biomass and bioactive compounds by microbial fermentation; hydrolysis and functionalization
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: Follows NIH Postdoctoral guidelines and comprehensive benefits Start date: As soon as possible Core Responsibilities Develop and optimize protein purification protocols for key stress response factors
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leverage the theory of estimating functions to create optimal inference algorithms for the proposed loss functions based on its underlying Riemannian geometry, as well as for those previously introduced in