Tenure-track position in Mathematical Sciences - Mathematical Finance (AY27/28)

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carnegie mellon universityPittsburgh (PA)

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About the role

Description: The Department of Mathematical Sciences at Carnegie Mellon University invites applications for an Assistant Professor position to begin September 1, 2027. This search will focus on the area of mathematical and computational finance, broadly construed. The Department has long-standing strength in this area, both in research and education. It plays a leading role in interdisciplinary educational programs in computational finance at the bachelor's and master's levels.
Qualifications: A Ph. D. in Mathematics, Statistics, or a closely related discipline is required. In general, preference will be given to candidates who have shown outstanding promise and/or excellent research accomplishments in stochastics, machine learning, and computing, and are pursuing a vigorous research program. The promise of excellent ability to teach and mentor students of varied backgrounds is a strong plus. Application Instructions Applicants should submit all materials electronically through Interfolio and Math Jobs (. This includes a cover letter, curriculum vita, list of publications, a statement describing current and planned research, a teaching statement. Candidates should also arrange for at least three letters of recommendation that will be solicited through Math Jobs. The review applications will begin on November 15, 2026. However, applications may be accepted and reviewed until the position is filled.
Equal Employment Opportunity: Statement Carnegie Mellon University is an equal opportunity employer. It does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, disability, age, sexual orientation, gender identity, pregnancy or related condition, family status, marital status, parental status, religion, ancestry, veteran status, or genetic information. Furthermore, Carnegie Mellon University does not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders.

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