The project-oriented research at the Weierstrass Institute is characterized by combining the mathematical disciplines of analysis, stochastics and numerics. This combination has great potential for solving complex applied problems such as the reliable extraction of information from large datasets or the suitable consideration of uncertainties in describing processes. In this way, the institute aids in solving current societal challenges.



The institute dedicates itself to fundamental mathematical research as well as the development of algorithms and scientific software. During the problem-solving process, mathematical models of physical and technological systems are designed that properly capture observed phenomena, thereby providing access to highly developed mathematical analysis. At WIAS the phases of the solving process are repeated and coordinated until an optimal solution is found.


Mathematical Core Areas

The WIAS is organised in eight Research Groups specializing in different mathematical techniques and methods. Additional temporary teams are created within a Flexible Research Platform as the need arises. The core areas of mathematical research are the analysis and numerics of partial differential equations, and stochastics.


Cooperation and Consulting

Modern applied mathematical methods are a fundamental resource and driving force for technological and economic development around the world. The rapid development of computer technology and mathematically based numerical methods are making it possible to numerically simulate ever more complex engineering, medical, economic and environmental problems.

At the WIAS excellent fundamental research is combined with years of experience in cooperating successfully with partners in the widest possible mix of application fields. The institute is therefore a recognized expert in the solution of complex economic, scientific, and technical problems by means of mathematical modeling and numerical simulation.



Mathematics our universal language!
New video clip from WIAS, produced for Berlin Science Week.


Wednesday, 30.11.2022, 10.00 (WIAS-ESH)
Forschungsseminar Mathematische Statistik
PhD M. Kasprzak, University of Luxembourg:
How good is your Laplace approximation? Finite-sample error bounds for a variety of useful divergences (hybrid talk)

further events


PhD student position (f/m/d) (22/24)
Data‐driven optimization and control; machine learning

PhD student position (f/m/d) (22/27)
Multicriteria Optimization Subject to Equilibrium Constraints Using the Example of Gas Networks

PhD student position (f/m/d) (22/29)
Stochastic gradient methods for almost sure state constraints for optimal control of gas flow under uncertainty

Research Assistant Position (f/m/d) (22/33)
data-driven and variational regularization methods for dynamic image reconstruction

Foreign language secretary (m/w/d) (22/35)
Research Group Numerical Mathematics and Scientific Computing

PhD student position (f/m/d) (22/37)
Equilibria for Distributed Multi-Modal Energy Systems under Uncertainty

Research Assistant Position (f/m/d) (22/39)
Theoretical and numerical study of photonic crystal surface-emitting semiconductor lasers (PCSELs)

Research Assistant Position (f/m/d) (22/40)
Optimization with partial differential equations and variational inequalities