Assistant Professors positions offered in 2020

The call is now closed. The selection process is completed

Applications in All Fields

The Einaudi Institute for Economics and Finance (EIEF) invites applications for two tenure-track position as Assistant Professor, starting in the summer of 2020. EIEF is an independent research foundation which produces academic research of the highest quality standards, with emphasis on policy-relevant topics. EIEF also offers courses at graduate level and runs high-quality conferences. It provides a pleasant and stimulating research environment, a top-notch visiting program, excellent facilities and premises located in the centre of Rome.

The position offers a competitive compensation package plus a research budget. Successful candidates are expected to publish their research in top peer-reviewed journals, teach graduate students (with a light teaching load) and contribute to the intellectual environment of EIEF. Applicants should have high research potential and have earned a Ph.D. degree in Economics or Finance or be close to completion. Applications in all fields are welcome. There are no restrictions regarding the nationality of the applicants. EIEF is an equal opportunity employer.

To apply, please submit a Curriculum Vitae, a completed research paper and three reference letters to EconJobMarket or, were this website not available, please submit your application directly to This email address is being protected from spambots. You need JavaScript enabled to view it. indicating “EIEF Assistant Professor positions 2020”. In both cases, the submission deadline is Friday, November 15th, 2019.

EIEF will interview shortlisted candidates at both the EEA Job Market, Rotterdam (Netherlands) December 18-19, 2019 and at the ASSA Annual Meeting, San Diego (USA) January 3-5, 2020. Please indicate your availability for interviews on either of the 2 markets.

Please note: candidates must also copy and include in their application the following Disclaimer concerning the processing of personal data.

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