AdresseThe Technical University of Munich (TUM) invites applications for the position of
Professor
in »Empirical Economics and Data Science «
W2 (with tenure track to W3) or W3 Associate/Full Professor; to begin as soon as possible. The professorship is endowed by the Dieter Schwarz Foundation and will be located at the TUM Campus in Heilbronn. Scientific environment
The professorship will be assigned to the TUM School of Management and affiliated with the Department of Economics & Policy. The scientific environment for the professorship will be the TUM Campus Heilbronn. The professorship is targeted to join the Heilbronn Data Science Institute. The school is listed as one of the leading business schools in Germany and internationally. We aim to create a real impact through our research, contributing to solving humanity’s greatest challenges. Existing members of the business school publish regularly in top business, economics, and general science journals. An interdisciplinary research environment awaits the successful candidate. The school has close ties to industry.
Responsibilities
Responsibilities include research and teaching, as well as the promotion of early-career scientists. We seek to appoint an outstanding scholar in the field of Empirical Economics and Data Science, with an emphasis on micro-econometrics and causal machine learning. An applied research focus on technology, innovation, and/or its impact on labor markets is desired. Teaching responsibilities include introductory courses in econometrics and statistics in TUM’s Bachelor in Management and Technology as well as courses in applied econometrics, machine learning, and/or economics of innovation and labor markets at the Master level, here in the Master in Management and Digital Transformation. A firm commitment to the Heilbronn Data Science Institute and active involvement in its build-up phase are greatly appreciated.
Qualifications
We are looking for candidates who have demonstrated excellent achievements in research and teaching in an internationally recognized scientific environment relative to the relevant career level (please see www.tum.de/en/faculty-recruiting-faq/ for further information).
A university degree, an outstanding doctoral degree or equivalent scientific qualification, and pedagogical aptitude are prerequisites. Substantial research experience abroad and strong knowledge of econometrics, Data Science applications, and causal machine learning techniques are expected, proven by publications in the leading international journals. We specifically value a proven ability to gain and lead cooperative research projects and to attract third party funding (DFG, EU, AiF).
Our Offer
Based on the best international standards and transparent performance criteria, TUM offers a merit-based academic career path for tenure track faculty from Assistant Professor through a permanent position as Associate Professor and on to Full Professor. The regulations of the TUM Faculty Recruitment and Career System apply. TUM provides excellent working conditions in a lively scientific community, embedded in the vibrant research environment at Bildungscampus Heilbronn, and close interaction with family-owned firms in the region. Services and core facilities will be shared in a center model. The TUM environment is multicultural, with English serving as a common interface for scientific interaction. TUM offers attractive and performance-based salary conditions and social benefits. The TUM Munich Dual Career Office (MDCO) provides tailored career consulting to the partners of newly appointed professors. The MDCO assists in the relocation and integration of new professors, their partners, and accompanying family members.
Your Application
TUM is an equal-opportunity employer and explicitly encourages applications from women. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude, and professional performance. Application documents should be submitted in accordance with TUM’s application guidelines for professors. These guidelines and detailed TUM Faculty Recruitment and Career System information are available at www.tum.de/faculty-recruiting. Here, you will also find TUM’s information on collecting and processing personal data as part of the application process.
Please submit your application by 14 April 2024 via the TUM recruitment portal: www.recruit.tum.de
