Technische Universität Dresden - Faculty of Computer Science, Institute of Artificial Intelligence, Cluster of Excellence “Centre for Tactile Internet with Human-in-the-Loop” (CeTI)
The TU Dresden is one of eleven German universities that were identified as an “excellence university”. TUD has about 36.500 students and almost 5319 employees, 507 professors among them, and, thus, is the largest university in Saxony, today.
Having been committed to sciences and the engineering before the reunification of Germany, TU Dresden now is a multi-discipline university, also offering humanities and social sciences as well as medicine.
Chair (W3) of Explainable Artificial Intelligence
Technische Universität Dresden as a University of Excellence is one of the leading universities in Germany, and is ranked among the 100 most innovative universities worldwide. Its distinguishing feature is a strong focus on research as well as its diversified offer of 129 courses of study in Engineering Sciences, Natural Sciences, Humanities & Social Sciences and Medicine.
It pursues a long-term overall development programme aimed at making TU Dresden an international top university.
At the Faculty of Computer Science, the Institute of Artificial Intelligence, for the Cluster of Excellence “Centre for Tactile Internet with Human-in-the-Loop” (CeTI), seeks to fill the Chair (W3) of Explainable Artificial Intelligence as a strategic chair at the earliest possible date.
This new chair will support the area of machine learning at the university and play a central role in the Cluster of Excellence CeTI. Research at CeTI aims at breakthroughs in improving collaboration between humans and machines in real, virtual and remote environments. The cooperation between humans and machines requires a mutual understanding in order to be able to predict actions, but also to provide insight into decision-making processes when an observed system behaviour does not meet expectations. It is expected that interactions between man and machine will in future very often be characterised by machine-learned models. The chair should therefore contribute in particular to the analysis of learned models using methods of machine learning, such as deep learning, to making statements as well as decisions made on their basis explainable, and to developing new methods of explainability in machine learning. Potential fields of research include the formalisation of interpretability, methods for the analysis of black-box models, evaluation of interpretable models, interpretable models from unsupervised and reinforcement learning, design of algorithms for interactive machine learning, human-centred machine learning as well as systems for online and interactive learning.
You will comprehensively represent the field of explainable machine learning in research and teaching. We wish for the future holder to play a central role within CeTI, close cooperation within the Faculty of Computer Science and in the School of Engineering Sciences is desired. In addition, the cooperation with the Faculty of Psychology and its research groups of Cognitive Neurosciences, as well as with Competence Center for Big Data (ScaDS) and the Center for Systems Biology Dresden (CSBD) are intended. Your teaching obligation for the current duration of the Cluster of Excellence will be reduced to four hours per week. You will teach courses on machine learning in German and English in all study programmes of the Faculty of Computer Science. Additionally, we expect your participation in teaching the foundations of computer science for students of computer science and other faculties. Your responsibilities also include participation in academic self-administration at the faculty and TU Dresden.
The position offers an excellent environment within the DFG-funded Cluster of Excellence. This includes the opportunity of interdisciplinary cooperation with computer scientists, cognitive neuroscientists, psychologists, mathematicians and engineers as well as access to state-of-the-art technologies and computing infrastructures. Further information on the Centre's research programme can be found at https://www.ceti.one/.
We are looking for an expert with a proven international track record in machine learning with experience in the research fields relevant to CeTI. We place special emphasis on international publications, active participation in the Cluster of Excellence and the independent acquisition of research projects in the above-mentioned fields. Excellent teaching capabilities are assumed, as well as a habilitation or habilitation-equivalent accomplishments. Applicants must fulfil the employment qualification requirements of § 58 of the Act on the Autonomy of Institutions of Higher Education in the Free State of Saxony (SächsHSFG).
How to apply:
For further questions, please contact the Dean of the Faculty of Computer Science, Prof. Dr. Uwe Aßmann, tel. +49 351 463-38215, email: email@example.com
TU Dresden seeks to employ more female professors. Hence, we particularly encourage women to apply. Applications from candidates with disabilities or those requiring additional support are very welcome. The university is a certified family-friendly university and offers a Dual Career Service. If you have any questions about these topics, please contact the Equal Opportunities Officer of the Faculty of Computer Science (Dr.-Ing. Iris Braun, tel. +49 351 463-38063) or the Representative of Employees with Disabilities (Roberto Lemmrich, tel. +49 351 463-33175). CeTI offers an intensive onboarding programme for newly appointed staff.
Please submit your application, including CV, description of your scientific career, a list of your scientific publications, and a list of courses taught, results of evaluations (preferably of the last three years) as well as a certified copy of the certificate of your highest academic degree as hard copy by 02.11.2020 (stamped arrival date of the university central mail service applies) to: TU Dresden, Dekan der Fakultät Informatik, Herrn Prof. Dr. Uwe Aßmann, Helmholtzstr. 10, 01069 Dresden and in electronic form (CD, USB flash drive or via the TU Dresden SecureMail Portal https://securemail.tu-dresden.de by sending it to firstname.lastname@example.org).
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application, including CV, description of your scientific career, a list of your scientific publications, and a list of courses taught, results of evaluations (preferably of the last three years) as well as a certified copy of the certificate of your highest academic degree as hard copy