The goal of this project is the development of stochastic gradient methods for the treatment of almost sure state constraints. Such constraints arise for example in the nomination validation of gas networks under uncertain demands but also play a role in the transition towards future hydrogen networks. A focus of the project is the consideration of sequences of relaxed problems intertwined with the stochastic gradient method and a rigorous mathematical convergence analysis of the resulting methods

Requirements:

We are looking for candidates with a master’s degree in mathematics or a closely related field with a strong background in optimization and partial differential equations. Prior knowledge in stochastic optimization, optimal control, or stochastic analysis is beneficial

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PhD student position (f/m/d) - Nonsmooth Variational Problems and Operator Equations The goal of this project is the development of stochastic gradient methods for the treatment of almost sure state constraints. Such constraints arise for example in the nomination validation of gas networks under uncertain demands but also play a role in the transition towards future hydrogen networks. A focus of the project is the consideration of sequences of relaxed problems intertwined with the stochastic gradient method and a rigorous mathematical convergence analysis of the resulting methods We are looking for candidates with a master’s degree in mathematics or a closely related field with a strong background in optimization and partial differential equations. Prior knowledge in stochastic optimization, optimal control, or stochastic analysis is beneficial

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