Deadline: January 15th, 2020. Job advertisement: https://stellenticket.de/69045/TUB/?lang=en Contact person: Prof. Schaeffter----- Technische Universität Berlin, Faculty IV - Electrical Engineering and Computer Science, Institute of Software Engineering and Theoretical Computer Science, and the PTB (National Metrology Institute) jointly invite applications for a 5-year position of a University Professor - salary grade W2 in the field of "Uncertainty, Inverse Modeling and Machine Learning". PTB is the National Metrology Institute of Germany with scientific and technical service tasks and supports society, industry, and science. The aim of the new professorship is to strengthen research in “biosignals, imaging and data analysis research” at the division of medical physics and metrological IT at PTB in close collaboration with TU Berlin. * Working field: Research in the field of “uncertainty, inverse modelling and machine learning” for the development and assessment of novel algorithms with applications in biomedicine, physics and/or metrology. Teaching responsibilities will focus primarily on courses in Electrical Engineering, Computer Engineering, Computer Science and/or Mathematics. The professorship will collaborate with the TU through the Berlin Centre for Machine Learning (Prof. Müller) funded by the Ministry of Education and Research (BMBF). Head of the department at the TU Berlin as well as lead of the work group "Machine Learning" at PTB. * Requirements: Candidates must fulfill the requirements for appointment at the professor level in compliance with § 100 BerlHG (Berlin Higher Education Act), including a finished academic education in Computer Science, Electrical Engineering, Physics, Mathematics or similar fields, qualified achievements in research (PhD), post-doctoral lecture qualification (Habilitation) or equivalent qualification (e.g. documented by the quality of scientific papers) and pedagogical didactic qualifications, documented in a teaching portfolio (for more information see TUB website, quick access no. 144242). Internationally acknowledged excellent research in machine learning, inverse modelling and uncertainty quantification with applications preferable in biosignals and imaging (e.g. EEG, MEG, ECG, MRT, CT). In particular, expertise is expected in the following areas: - Machine learning algorithms (e.g. deep learning, kernel methods, reinforcement learning, dimensionality reduction) and their applications, - Influence of data uncertainty on machine learning algorithms, - Explainability of machine learning, - Solving inverse problems with machine learning, - Simulations for assessment of machine learning methods. Third-party research funding is expected. The willingness to offer teaching in German as well as in English language is also a prerequisite. Very good English language skills are required. The willingness to learn German is expected from Non-German speaking applicants. *How to apply: Technische Universität Berlin is determined to increase the proportion of women in research and teaching and therefore strongly encourages qualified female researchers to apply. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Technische Universität Berlin is a certified family-friendly higher education institution, and our Dual Career Service offers assistance to you and your family when relocating to Berlin. Applications from abroad are explicitely welcome. Please send your written application by 15th January, 2020 indicating the reference number IV-550/19 and including the appropriate documentation (CV listing publications etc., copies of academic degrees, as well as copies of up to five selected publications, teaching portfolio and draft of prospective teaching and research projects) preferably by e-mail as PDF to berufungen@eecs.tu-berlin.de. Alternatively, applications may be submitted in writing together with a digital version to Technische Universität Berlin – Der Präsident –, Dekan der Fakultät IV, Prof. Dr. Rolf Niedermeier, Sekr. MAR 6-1, Marchstraße 23, 10587 Berlin. Please send copies only. Original documents will not be returned.