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Access Program vendors, Criteria review for Value Analysis, Clinical Case Reviews, Complex Billing (Medicare A to B, ASAM) Complex Denials, Clinical Appeals. RCCS is responsible for responding
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involves mathematical modeling and numerical simulation, but also the analysis of experimental datasets for model validation. Your Profile: A Masters degree with a strong academic background in physics
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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journals and presenting at the most well-regarded conferences. Strong background in structural mechanics, analysis of complex structures, and structural design. Proven track record of working effectively
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analysis. • Hydrological and hydraulic simulation. • Machine learning, including unsupervised clustering and predictive modelling. • Working with large, complex, multi-source datasets using MATLAB, Python
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(or are close to completing a PhD) in pure or applied mathematics, with an excellent profile in functional/complex analysis and fields related to the project (such as, but not limited to, numerical linear algebra
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, combinatorics, partial differential equations, stochastics and risk, algebra, geometry, topology, operator algebras, complex analysis and logic. We have almost 50 persons in permanent academic positions and a
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of diverse scope where analysis of data requires a thorough understanding of complex regulations. We are seeking a collaborative, professional, team player. The incumbent should be proactive, understand
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). You can find more details below, as well a short presentation of the project. Non-Gaussian self-similar processes : Enhancing mathematical tools and financial models for capturing complex market
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to augment classical spike train analysis methods particularly those developed by Prof. Grün and others for detecting synchronous spiking activity with AI-based enhancements. After profiling the classical