Technical University of Dresden

Technical University of Dresden

The Technical University of Dresden, in the city of art and science, has completely reorganized its 18 faculties in five fields in order to improve and simplify interdisciplinary cooperation. Hardly any other German university can offer such an integrated range of courses as TUD: here engineering sciences, mathematics and natural sciences, humanities and medicine are all under one roof. A special focus of the university is on the individuality of each of the approximately 32,000 students. That’s why they can apply for any of the 121 courses of study to further develop their own personality. The university is committed to equal opportunities and work-life balance. For example, female students are supported in order to increase their numbers at the university, especially in the fields of computer science, engineering and natural sciences. Moreover, the Technical University of Dresden particularly supports young families in reconciling studies and family life. As a result, it has been certified as a family-friendly university since 2007.

The university is one of the eleven universities of excellence in Germany and pursues its concept for the future by “building bridges”, which is intended to connect not only people, but also science, business, East and West, as well as generations through education. The TU Dresden is a partner in the DRESDEN concept – a unique network in Germany to which all four major German scientific societies (Fraunhofer Association, Max Planck Association, Leibniz Association and Helmholtz Association) belong. The synergy with non-university institutions, the interlinking with industry and interdisciplinary research and teaching play an extremely important role.

With more than 1,600 students, the Faculty of Computer Science is one of the largest educational institutions for computer science in Germany. Its research interests include software technology, the Internet of Services, cloud computing and security, data-intensive computing and big data, knowledge extraction, human-computer interaction and visual computing, formal modeling and analysis, and machine learning and simulation.