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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 7 days ago
, or similar software. • Knowledge in SPARTA (Stochastic PArallel Rarefied-gas Time-accurate Analyzer) and DAC (DSMC Analysis Code), or similar tools. Point of Contact Mikeala Eligibility Requirements
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Helmholtz Association of German Research Centres | Potsdam, Ohio | United States | about 2 months ago
meteorological processes and flood risk concepts Experience in statistics, particularly extreme value statistics, and stochastic simulation Knowledge in using stochastic weather generators Experience with climate
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on the development of continuum and discrete, stochastic mechanical models of ordered cellular structures and understanding the role of order in pattern formation. The project is in close collaboration with
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
following areas: High-dimensional probability and concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations
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physics. Candidates for the position must have a PhD in physics or a related discipline, preferably with expertise in stochastic processes, nonlinear dynamics, and biological physics. The intended start
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candidate will have a strong foundation in statistical mechanics, stochastic processes, dynamical systems, complex systems, or related quantitative approaches; Experience in developing and implementing
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modeling, computational modeling, quantitative biology, dynamical systems, stochastic processes, complex systems, or related quantitative approaches. Candidates should have experience developing
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of mathematical modeling, with a particular focus on stochastic modeling, optimization and more recently machine learning. Indeed, over the last years, the team’s activity has been marked by a strong shift toward
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to enable scalability. The work will draw on concepts from dynamical systems, stochastic processes, and stochastic differential equations (SDEs), including nonequilibrium systems, to model cellular behavior
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models