Chair in Machine Learning for Spatial Understanding at TECHNISCHE UNIVERSITAT DRESDEN (TU DRESDEN)

TU Dresden is among the best universities in Germany and Europe and one of eleven German universities with the title “University of Excellence”.

The Faculty of Computer Science invites applications for the

Chair (W2/W3) of Machine Learning for Spatial Understanding

is to be completed as soon as possible as a strategic chair at the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI Dresden/Leipzig). The position offers an excellent environment within the ScaDS.AI competence center in Dresden/Leipzig, which is funded by the Federal Ministry of Education and Research and the Free State of Saxony. This includes the possibility of interdisciplinary cooperation with computer scientists, natural scientists, mathematicians and scientists from the life sciences, medicine, environmental sciences, earth sciences and engineering. There is access to state-of-the-art technologies and an exceptional high-performance computing infrastructure. Further information on the search directions of ScaDS.AI can be found at

The new chair will support the field of artificial intelligence (AI) and machine learning (ML) at the university and play a central role in the ScaDS.AI center in Dresden/Leipzig. In order to bridge the gap between the effective use of Big Data, advanced AI methods and knowledge representation, a total of eight new Chairs in the fields of data analytics and artificial intelligence will be created. on both ScaDS.AI sites. This will strengthen the methodological orientation in Big Data, machine learning and artificial intelligence. At TU Dresden, fundamental research areas are to be established by four new chairs in “Data Science”, “Knowledge-Aware Artificial Intelligence”, “Scalable Software Architectures for Data Analytics” and “Machine Learning for Spatial Understanding”. In particular, it will also advance the use of AI methods in various application areas.

The Chair of Machine Learning for Spatial Understanding will research and develop robust, efficient, and scalable methods for the machine understanding of three-dimensional structures, scenes, and objects using machine learning methods. We are particularly interested in the following research topics and their application to autonomous driving, industrial automation, robotics, diagnostics and medical intervention: Efficient machine learning for point cloud analysis and depth maps; Simultaneous Localization and Mapping (SLAM); Machine Learning for recognizing deformable objects; multimodal spatial reconstruction, esp. using light, radar and ultrasound; robust spatial reconstruction using sensor fusion; understanding of the semantic scene; adaptive spatial reconstruction; and robotic navigation. You must have made significant research contributions in one or more of these areas.

You (m/f/x) will represent the subject of the call for research and teaching. The chair should play a central role in ScaDS.AI Dresden/Leipzig and integrate with the Faculty of Computer Science. Within the framework of the competence center there is close cooperation with various disciplines. The teaching obligations are reduced to two hours/week for the duration of the ScaDS.AI Dresden/Leipzig, but participation in teaching is desired. This includes courses in German or English in the area of ​​dedication for the programs of the Faculty of Computer Science. In addition, as is standard, you will teach core courses in the field of dedication and in other faculties (export education). In particular, we expect the chair to contribute to the development of the new “Data Science” course and the new “Applied AI” course of the Master’s “Computational Modeling and Simulation”. Responsibilities also include participation in academic self-administration and academic committees of the Faculty of Computer Science and Technische Universität Dresden.

You are internationally recognized in the mentioned research areas and have experience in one or more application areas relevant to ScaDS.AI Dresden/Leipzig. Particular emphasis is placed on excellent international publications as well as active participation in collaborative interdisciplinary research, as well as the independent acquisition and management of research funding. The candidate must have substantial experience in supervising doctoral students, proven excellent teaching abilities and a habilitation or achievements equivalent to a habilitation. The prerequisites for the appointment are based on § 58 of the Self-Government Act for Higher Education Institutions in the Free State of Saxony (SächsHSFG).

The president is usually appointed to a W2 post. An upgrade to a W3 position may be considered if the ScaDS.AI criteria of excellence are exceptionally met: outstanding research output, proven success in mentoring junior scientists, high international visibility, coverage of a domain broader research, and also innovative. like and preferably interdisciplinary research approaches.

For any questions, please contact the Dean of the Faculty of Computer Science, Prof. Dr sc. tech. Ivo F. Sbalzarini, tel. +49 351 463-32815; E-Mail: [email protected], as well as the director of ScaDS.AI, Prof. Dr. rer. nat. Wolfgang E. Nagel, tel. +49 351 463-35450; Email: [email protected]

TU Dresden seeks to employ more female teachers. Therefore, we particularly encourage women to apply. Applications from candidates with disabilities or requiring additional support are welcome. The University is a certified family-friendly university and offers a dual career service. If you have any questions on this or related topics, please contact the Equal Opportunities Officer of the Faculty of Computing (Dr.-Ing. Iris Braun, +49 351 463-38063) or the representative of people with disabilities (Mr. Roberto Lemmrich, Tel.: +49 351 463-33175).

Please submit your application including the usual documents (curriculum vitae in tabular form, description of your scientific career, list of publications, list of third-party funded projects and previous teaching activities, including the results of teaching evaluations (preferably from the last three years)), a concept of research (max. 3 pages), of integration and teaching (max. 1 page each) as well as a certified copy of the certificate of your most recent university degree raised by August 22, 2022 (date of receipt by the central postal service of TU Dresden) to: TU Dresden, Dean of the Faculty of Computer Science, Prof. Dr. Ivo F. Sbalzarini, Helmholtzstr. 10, 01069 Dresden, Germanyand in electronic form (CD, USB storage medium or via the SecureMail portal of TU Dresden, to [email protected]).

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