168 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"I.E" positions at NIST in United States
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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NIST only participates in the February and August reviews. The modern transmission electron microscope (TEM) is capable of atomic-resolution structural and chemical imaging. However, such data
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. A key challenge is the integration of prior knowledge into the data analysis, including both device physics and material properties.We are primarily interested in photonic (e.g. silicon ring
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data analysis techniques, instrument and sample environment development, and simulation methods to compare to experimental results. We are particularly interested in the development of two techniques
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integrated nanophotonic devices and systems with novel mechanisms to generate, detect and manipulate light on chip, for classical and quantum information processing. All projects involve development of new
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Development of magnetism-based future electronics is fueled by demand for large memory capacity and high data processing rates. New technologies such as hard drives with bit-patterned media and magnetic memory
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technique. Multimodal imaging combines information from two or more imaging modalities such as MRI, computed tomography (CT), positron emission tomography (PET), and ultrasound (US). These combined techniques
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Entanglement; Metrology; Quantum information; Quantum state; Single photon; Single photon detector; Single photon source; Eligibility citizenship Open to U.S. citizens level Open to Postdoctoral applicants
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andrei.kazakov@nist.gov 303.497.4898 Description Empirical correlations derived from existing experimental data have always played an important role in thermophysical property estimation. These empirical
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experiments and datasets for model validation of multi-phase computation fluid dynamics (CFD), discrete element method (DEM), or data-driven modelling. Measurement of defect types and populations using micro- x