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Field
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on the Gerchberg-Saxton algorithm, and then building out an optical setup to test whether these phase patterns can successfully turn a Gaussian beam into the arbitrary predicted patterns. 25% - Building an optics
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. - Strong proficiency in machine learning, optimization algorithms, and computational modeling applied to construction systems. - Experience with designing and conducting experimental studies to evaluate
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optimizing these patterns based on the Gerchberg-Saxton algorithm, and then building out an optical setup to test whether these phase patterns can successfully turn a Gaussian beam into the arbitrary predicted
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outcome research, including classification, regression, clustering, and deep learning algorithms. · Statistical Software: Proficiency in statistical software such as SAS, Stata, R or Python, including
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learning including reinforcement learning, nature inspired algorithms, deep learning, agent based modeling, and natural language processing. We are specifically interested in research focused
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dynamics (algorithms and current practice). Experience in AI/ML. Experience in application performance optimization. Familiarity with parallel programming models (e.g., OpenMP, MPI, CUDA). Experience
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climate observations, numerical modeling, machine learning algorithms, and decision support tools focused on atmospheric, land-surface, and hydrologic conditions related to extreme weather events and their
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experience from which comparable knowledge is demonstrated may be considered. Preferred Qualifications Ph.D. degree. Demonstrated expertise in computational biophysics and molecular dynamics (algorithms and
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questions in quantum information science, and to guide near-term hardware and algorithm co-design. What You Will Do: Design of superconducting electronic devices with emphasis on superconducting quantum
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interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology