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Field
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variety of conditions that are not optimal growth conditions. The survival data of pathogens under these conditions (growth matrices + sub-optimal growth temperatures + antimicrobial stresses) will also be
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genomic approach to profile enhancer dependencies. Develop and optimize experimental workflows integrating scRNA-seq, scATAC-seq, and other single-cell omics. Interpret high-dimensional data in
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electrolyte and polyanion or oxide-based cathode materials. Project aims to optimize synthesis conditions for scale-up production of solid electrolytes (ceramic and polymer electrolytes) and positive/negative
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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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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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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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will develop a novel modelling framework that translates climate signals to support cost-optimal long-term investment decisions, while also considering operational feasibility. The successful candidate
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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
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environmental benefits by the increasing use of recycled asphalt binders in new pavements. Under the guidance of a mentor, the participant will participate in the development and optimization of chemical