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NSF-RTG Postdoctoral Position in Applied Analysis (AY27/28)

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NSF-RTG Postdoctoral Position in Applied Analysis (AY27/28)

Carnegie Mellon University
Published
October 31, 2026
Expires
Never
Location
Pittsburgh, PA

Description

**Description**

The Department of Mathematical Sciences at Carnegie Mellon University invites applications for a two-year postdoctoral position to begin on September 1, 2027. The position is focused on applied analysis and related areas of applied and computational mathematics. The position is connected to the NSF RTG grant "Frontiers of Applied Analysis". Consequently only U.S. citizens, nationals, and permanent residents are eligible. Depending on the expected continuation of funding and performance, the position may be extended to the third year.

**Qualifications**

Ph.D. in mathematics or a closely related discipline is required.

Preference will be given to candidates who have shown outstanding promise and/or excellent accomplishments in research in a broad spectrum of applied and computational mathematics. This includes PDE, calculus of variations, probability and stochastic analysis, numerical analysis, and scientific machine learning. Interest in interdisciplinary efforts is also valued. Commitment to and experience in teaching and mentoring student research are also desirable.

**Application Instructions**

Applicants should submit all materials electronically through both Interfolio and MathJobs. (https://www.mathjobs.org/jobs/list/29398) This includes a cover letter, a curriculum vita, a list of publications, a statement describing current and planned research, and a teaching statement. Candidates should also arrange for at least three letters of recommendation that will be solicited through MathJobs.

The review applications will begin on December 1, 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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