Professor in » Empirical Economics and Data Science «

at  Technische Universitt Mnchen

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.

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).

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.