|
Münster (upm/vl).
Scientists celebrated the news from the DFG that the new Research Training Group will be funded.<address>© Uni MS - Julia Schleuß</address>
Scientists celebrated the news from the DFG that the new Research Training Group will be funded.
© Uni MS - Julia Schleuß

German Research Foundation approves Research Training Group

More than four million euros for doctoral programme in mathematics at the University of Münster

Good news for Mathematics Münster: The German Research Foundation (DFG) has approved a new Research Training Group dedicated to educating mathematicians in the fields of probability theory and applied analysis. The research goal is to advance both qualitative and quantitative analyses of complex random systems with macroscopic variables, unveiling deeper insights into the nature of these intricate mathematical constructs. The programme, entitled "Rigorous Analysis of Complex Random Systems," will receive more than four million euros in funding for an initial five-year period starting in October 2025, as announced by the DFG today. The spokesperson of the programme is Prof. Dr. Martin Huesmann from the Institute for Mathematical Stochastics.

Spokesperson of the new Research Training Group “Rigorous Analysis of Complex Random Systems”: Prof. Dr. Martin Huesmann.<address>© Uni MS - Victoria Liesche</address>
Spokesperson of the new Research Training Group “Rigorous Analysis of Complex Random Systems”: Prof. Dr. Martin Huesmann.
© Uni MS - Victoria Liesche
"In recent years, the amount of data and information that needs to be analysed on a daily basis has increased enormously. As a result, there is an increasing need for mathematically tractable models that allow such analyses to be carried out, as well as for specialists who can develop these models and adapt them to specific situations," says Martin Huesmann. The new Research Training Group aims to provide doctoral researchers with a comprehensive understanding of the analysis of complex systems, offering them excellent starting conditions for careers both within and beyond academia.

The central research theme of the Research Training Group is a mathematically rigorous understanding of how random systems modelled on a microscopic level behave effectively on larger scales. Research projects are situated in areas such as statistical mechanics, where systems comprising an astronomical number of particles can be described on macroscopic scales by just a few observables. Other projects explore topics like the homogenisation of mathematical models in materials sciences or the behavior of training algorithms in machine learning. "What makes this program unique is that the techniques and underlying mathematical ideas are universally applicable across the various projects," emphasizes Martin Huesmann.

Over the next five years, 20 doctoral candidates and two postdoctoral researchers will have the opportunity to participate in the qualification programme. It includes specialised courses, regular seminars, working groups, and annual retreats. "In addition, they will benefit from the lively mathematical community in Münster," says Martin Huesmann. "The Cluster of Excellence Mathematics Münster, in combination with the new graduate school, offers an outstanding and inspiring research environment. It enables participation in a mentoring programme and several interaction and networking activities with other mathematical fields and local industry."

Structured Doctorates at the University of Münster

Research Training Groups are institutions of higher education for the promotion of young scientists. They are funded by the DFG for a maximum of nine years. The focus is on the qualification of doctoral researchers within the framework of a thematically focused research programme and a structured qualification concept. With the approval of this new programme, the University of Münster currently hosts four DFG-funded Research Training Groups. In addition, the University of Münster offers numerous other structured doctoral programmes, funded either by the university or through third-party funding.

Further information