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, computational fluid dynamics and material science, dynamical systems, numerical analysis, stochastic problems and stochastic analysis, graph theory and applications, mathematical biology, financial mathematics
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integration Optimization and stochastic modeling methodologies Energy storage Electricity market analysis Supports multidisciplinary teams in the application of these methods and tools to complex issues in
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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WIAS Berlin, Weierstrass Institute for Applied Analysis and Stochastics Position ID: 2306 -RAP2 [#26751, 25/10] Position Title: Position Location: Berlin, Berlin 10117, Germany [map ] Appl Deadline
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area of Drosophila neural development: How are stochastic choices made in sensory neuronal development coordinated with the deterministic generation of neuronal diversity in the synaptic targets
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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techniques may be employed to support the modeling of uncertainty, along with the formulation and resolution of planning problems using stochastic optimization methods. Key Responsibilities The selected
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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Boltzmann and Landau kinetic theory, dynamic mean-field theory and the theory of stochastic processes including Fokker-Planck Equations and path integral techniques. However, applicants from other areas
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methods, stochastic control processes, dynamic programming, deep reinforcement learning. Strong track record in scientific contributions supported by peer-reviewed publications. Strong programming skills