Go to JKU Homepage
Institute for Algebra
What's that?

Institutes, schools, other departments, and programs create their own web content and menus.

To help you better navigate the site, see here where you are at the moment.

Welcome at the Institute for Algebra


Algebra is one of the conventional branches of mathematics. We represent this area in research and education, providing the theoretical foundations used in many other areas of science.


Our institute covers several areas in the field of algebra, including a focus on computer algebra, to develop algorithms that support the automatic solution of algebraic problems. Another focal point is Universal Algebra, focusing on abstract generalizations of conventional algebraic structures. A third focus includes the theory of nearrings, an area in Linz which has advanced significantly over the past decades.


Institute for Algebra


Johannes Kepler University Linz
Altenberger Straße 69
4040 Linz


Science Park 2,  3rd floor, Room 372

Office Hours

Tuesday: 12:00 - 5:00 PM
Wednesday: 7:30 AM - 3:30 PM
Thursday: 1:00 - 6:00 PM


+43 732 2468 6850

News 08.04.2024

Ph.D. student positions available

We are looking for people who are interested in doing their Ph.D. on a hot topic in the area of computer algebra.

News 23.03.2024

Algebra is child's play

It's never too early to get started. Today Prof. Kauers gave a lecture on algebra at a local Kindergarten.

Algebra is child's play
News 21.03.2024

Bernardo Rossi completed his Ph.D. studies

On March 21st, 2024, Bernardo Rossi successfully defended his PhD-thesis "Universal Algebraic Geometry and Polynomial Interpolation".

Bernardo Rossi PhD
News 13.03.2024

New FWF-project granted

In its most recent board meeting, the Austrian Science Fund FWF has granted a research project on "Constructive Decomposition of Matrix Multiplication Tensors". The project was proposed by Manuel Kauers in collaboration with Jakob Moosbauer.

The goal of this project is the development of advanced search techniques for writing a given tensor as a sum of rank-one tensors. This is the key step in the development of fast matrix multiplication algorithms.