ENSAE Paris and CREST are recruiting an Assistant Professor (tenure-track) in the field of Artificial Intelligence applied to finance. The recruitment benefits from the financial support of Hi!Paris, Paris Artificial Intelligence center for Society and Business.
Candidate Profile
Candidates should have a recognized research activity in machine learning and its applications to finance or in financial modeling based on AI tools. We aim for publications in leading journals across several fields, including machine learning and computer science (e.g., JMLR, JAIR, Pattern Recognition), quantitative finance (Mathematical Finance, Finance and Stochastics), and financial/stochastic modeling (Annals of Applied Probability, Journal of Econometrics, JBES). We also target established journals in broader disciplines such as Journal of Finance, Management Science, and Annals of Operations Research.
CREST is an interdisciplinary lab that includes teams in economics, finance and insurance, statistics and machine learning. The candidate should be able to interact scientifically with colleagues specialized in finance, statistics, and computer science at CREST and other labs of Institut Polytechnique de Paris.
Teaching duties
The recruited candidate will teach in the ENSAE engineering program as well as in partner master programs at Institut Polytechnique de Paris.
Terms and conditions
The appointment starts no later than September 1, 2026. Salary is competitive according to qualifications. Teaching duties are significantly reduced compared to French university standards. The incumbent will have access to substantial research funds covering in particular the funding of a doctoral student.
The position is attributed for an initial three-year term (during which teaching duties is reduced by half if the PhD was obtained less than 3 years earlier), renewable for another three years (with full teaching duties) before the tenure evaluation based on publication track record as well as teaching feedback.
Candidate Requirements
PhD in Applied Mathematics, Quantitative Finance, Computer Science, Financial Econometrics.
Publications or potential to publish in leading international journals in Machine Learning, Applied Probability, Finance, Econometrics and/or Statistics.
Ability to teach Machine Learning/AI/Quantitative Finance at the undergraduate and graduate levels, and to supervise student projects in these areas.
- Curriculum vitae
- Teaching evaluations
- Research proposal
- Cover letter (optional)
- Job market paper
- Letters of reference: 3