Duties: Modeling of fundamental electrochemical systems with partial differential equations; Development of material models for electrolytes and electrodes; Validation of the derived models using suitable experimental data; Systematic model simplification using asymptotic methods, e.g. derivation of effective boundary conditions, homogenization of microscopic models
Requirements: Candidates with a PhD in mathematics, scientific computing, theoretical physics, or related fields, and published research contributions in peer-reviewed journals are sought. In-depth scientific experience in modeling electrochemical systems with partial differential equations as well as a high interest in applications of mathematics are expected

Duties: Studying systems in a game-theoretical context involving physical constraints taking the form of partial differential equations with uncertainties; Analyzing distributed stochastic models where agents do not share all information but need to find equilibrium strategies; Developing and implementing novel distributed algorithms to find equilibria computationally
Requirements: A motivated, outstanding student with a master’s degree in mathematics. A strong background in the theory and numerics of partial differential equations and a very good background in optimization and/or stochastic analysis is required

Duties: The Weierstrass Institute conducts project oriented research in applied mathematics with the aim of solving complex problems in technology, science and the economy. The institute deals with the whole scientific solution process, starting with mathematical modeling, followed by the theoretical analysis of models, and ending with the numerical simulation of the solution. In this context, the WIAS maintains long term, wide-ranging contacts with those who apply mathematics in industry and other areas of research and for whom it is a reliable partner
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Duties: Optimization with partial differential equations and variational inequalities. The holder of the position is qualified in a modern field of optimization with partial differential equations. Of particular interest are non-smooth coupled systems and data-driven (e.g. machine learning) approaches to modeling and optimization, variational problems in mathematical image processing or nonlinear inverse problems. In addition to analytical considerations, the development and implementation of numerical solution methods are of central importance
Requirements: A motivated, outstanding researcher with a very good degree and excellent doctorate in mathematics as well as previous experience in the fields mentioned above with the willingness to take on responsibility for interdisciplinary projects. Further experience within the framework of independent research in a postdoctoral phase is desired as well as very good knowledge in one or more of the areas: Optimal control with partial differential equations, (Quasi-)Variational inequalities and their optimal control, Non-smooth variational problems with applications in image processing