Testimonials Master’s degree programme Mathematics

Tag Archive for: MA-MATH

Making better use of energy thanks to optimisation methods: new MSCA doctoral network ALMOA approved

ALMOA (Advances in Large-scale, Multilevel, and Hierarchical Optimisation for Challenging Applications) is set to be launched in January 2026. It is the first doctoral network coordinated by the University of Klagenfurt that is funded by the EU through Horizon Europe as a Marie Skłodowska-Curie Action. Thirteen doctoral students will be conducting research on mathematical optimisation issues at thirteen European universities. The project has two aims: the new algorithms should help to make logistics and transport more sustainable, energy systems more efficient, and data processing more resource-efficient. At the same time, the doctoral students will benefit from an excellent training network, providing them with valuable cross-sector insights. 

Read more

Advice on studying before the start of the semester: ÖH Info Days!

The Info Days of the Austrian Students’ Union (ÖH) at the University of Klagenfurt/Celovec, the lobby group in university politics for all students at our university, will support you on 17 July and 3 & 4 September 2025 before the start of the semester with advice on all aspects of studying.

Read more

Improving magnetic resonance imaging with mathematics

The special research area “Mathematics of Reconstruction in Dynamical and Active Models”, funded by the Austrian Science Fund FWF, was launched in March 2025. Researchers from the University of Klagenfurt, led by Barbara Kaltenbacher (Department of Mathematics), will be contributing their expertise on inverse problems. The aim is to develop new mathematical tools for active, dynamic and model-based imaging modalities.

Read more

Using innovative methods to improve our understanding of the interplay between monetary policy and the economy

How can we improve the prediction of systemic risks in financial and economic crises? A new research project is developing innovative Bayesian methods to model dynamic covariances – with the aim of improving forecasts and supporting political decisions.

Read more