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of scientific programs in Matlab or similar programming language. Interest in signal processing algorithm design and development. Interest in acoustic data processing and analysis, and SONAR system design and
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algorithms, security of AI-enabled CPSes and related peripherals; cybersecurity. We search for applicants who will contribute to our academic programs, promote transdisciplinary teaching and research, and help
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research scientist. This is a unique opportunity to contribute to cutting-edge research in super-resolution cavitation mapping. You’ll work on computational projects that involve developing algorithms
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that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance and edge computing; The design of architectures
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investment, risk management, and operations functions of the Office of University Investments (OUI) and contribute to the development and maintenance of analytical tools and applications that support the
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into refining computational strategies for large-scale molecular simulations in materials science and computational physics. The project will involve substantial numerical development, including algorithm design
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-depth understanding of data and related algorithms, data analysis, and machine learning. Our cross-cutting theme is machine learning-enhanced computational engineering. You’ll have an excellent
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8351HE Employee Class Civil Service Add to My Favorite Jobs Email this Job About the Job Job Description: This position will be in charge of developing energy determination algorithms for the Liquid Argon
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-leading neuroscience department where molecular, anatomical, and physiological discoveries are seamlessly integrated into developing new treatments for neurological diseases. This research position will be
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University of Southern California (USC) | Los Angeles, California | United States | about 2 months ago
. The incumbent will develop and implement algorithms on existing data warehouse records and may nominate new external data sources to be ingested to the data warehouse to strengthen analyses. Analyses will address