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. Preferred backgrounds include nonlinear optics, quantum optics, spectroscopy, or instrumentation. Proficiency in software and coding (e.g., MATLAB, LabVIEW, Python) is expected. Applicants with a strong
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research focuses on a geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics
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geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics. Qualifications: - Applicants
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management and coding, machine learning AI, and familiarity with LSST data management image reduction and analysis tools. Familiarity with processing data at the DOE US Data Facility at SLAC National
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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial
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have the opportunity to travel to relevant national and international events and conferences, with a special focus on meeting and networking opportunities in the Gulf of Mexico region. Relationship