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.), Physics I (particle, nuclear, astrophysics, etc.), Physics II ( condensed matter, etc.), Chemistry, Biology (cell biology, developmental biology, plant biology, structural biology, microbiology, imaging
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collaborative environment with projects and interactions spanning multiple labs within the group, across NIST and externally. Candidates should have a PhD in physics, electrical engineering, mechanical
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of materials. We are searching for a Postdoctoral Researcher with excellent numerical skills and a deep understanding of condensed-matter physics concepts. Experience in machine learning, DFT, symmetry aware
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reconstructions. Specific complexes will be approached by sub-tomogram averaging and single-particle analysis when relevant. The project will entail the following specific aims: Ultrastructural insights
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learning models (e.g., PCA, PLS-DA, clustering, CNNs) to classify microplastic particles based on spectral and morphological fluorescence data. Develop and maintain modular analysis pipelines in Python
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do research that matters. Our work covers a broad array of topics in the focus areas of energy, infrastructure, environment, materials, and chemistry and process engineering. We are looking