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Department of Mathematics
Technical University of Munich

Elite Programs

The Department of Mathematics participates in a number of elite programs. These offer excellent graduates a well solid education in maths, in which they can make contacts within the field and complete their studies with a Masters or PhD qualification. The requirements for acquiring a place in one of our elite study programs include very good academic achievements and an active, socially-orientated life alongside your studies. 
 

TopMath

Eliteprogramm TopMath - Logo

TopMath is a study program of the Elite Network of Bavaria. It enables excellent Bachelor students to start a PhD directly after graduating. TopMath supports students in the fields of pure and applied mathematics and in related areas in informatics. Internationally renowned professors at the TUM and the University of Augsburg offer TopMath students many opportunities to pursue their interests in research.

Finance and Information Management

Finance and Information Management (FIM)

The elite program Finance & Information Management (FIM) offers outstanding Bachelor graduates an interdisciplinary education, which is completed with the award Master of Science. The lectures and seminars are held by national and international speakers from prestigious universities. This unique study program is the perfect preparation for students looking for leading jobs in business, science or politics. 

Current news from our department

To overview
Versicherungsmathematik-Workshop in Hamburg von der TUM Einrichtung ERGO Center of Excellence in Insurance
© ERGO Center of Excellence in Insurance

Workshop Actuarial Mathematics

Registration deadline is 15th March! Take part in the workshop with our cooperation partner ERGO and get to know the work of actuaries.
Studieninfotag 2019: Schülerin mit Mappe und Rucksack - Symbolbild
© pixabay.com

Studieninfotag 2019

Im Hörsaal Vorträgen lauschen und Forschung erleben wie ein*e Student*in: Am Studieninfotag schnuppern Schüler*innen Uni-Luft. Besucht uns am 28. März 2019!
Single-cell RNA-seq denoising using a deep count autoencoder: DCA denoises scRNA-seq data, Fig. 1 aus Eraslan, G.; Simon, L.M.; Theis F. et al. (2019): Single cell RNA-seq denoising using a deep count autoencoder. Nature Communications.
© Eraslan, Simon, Theis et al.: Single cell RNA-seq denoising using a deep count autoencoder. Nature Communications.

AI against errors

Using single-cell analysis, researchers study the behavior of cells. But the method is prone to errors. A deep learning algorithm can now detect these errors.
Bildmotiv TopMath

Independent Studies: Vorträge

The Independent Studies form the core of the elite study program TopMath. The students present the results of their studies in a talk, which is open to a general university audience.