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"Postdoctoral Position in Applied Analysis (funded by NSF) - AY26/27"

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Postdoctoral Position in Applied Analysis (funded by NSF) - AY26/27

Description

The Department of Mathematical Sciences at Carnegie Mellon University invites applications for a two-year postdoctoral position to begin on September 1, 2026. 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. This includes a cover letter, a curriculum vitae, 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 November 15, 2025. 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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