Austria: Tenure Track Position in Data Driven Partial Differential Equations

We are looking for outstanding scientists who are active in the development of mathematical models or numerical methods in partial differential equations, in connection with uncertainty or data science. Specific fields of interest include, but are not limited to, stochastic partial differential equations, optimal transport, gradient flows, uncertainty quantification, model order reduction, data assimilation, optimal control, and their applications.

The successful applicant is expected to complement the faculty’s ongoing research activities in the field of applied and computational PDEs. Current research covers a wide range of applications, including biology, materials science, and astrophysics, and uses a variety of approaches, such as stochastic processes, kinetic theory, variational analysis, finite element methods, and data-driven techniques. The Vienna School of Mathematics offers excellent conditions for doctoral training at the highest level in all areas of mathematics and promotes interdisciplinary and intradisciplinary cooperation.

Further information on the position, how to apply and the full advertisement may be found at: https://jobs.univie.ac.at/job/Tenure-Track-Professorship-in-Data-
Driven-Partial-Differential-Equations/1417564533/