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Stochastic Computational Methods for Nonlinear Multiscale Mechanics

ABG-75382 Sujet de Thèse
12/02/2018 > 25 et < 35 K€ brut annuel
Duke University
Durham - Etats-Unis d'Amérique
Stochastic Computational Methods for Nonlinear Multiscale Mechanics
  • Numérique
  • Physique
  • Sciences de l’ingénieur
computational mechanics, uncertainty quantification, stochastic analysis, multiscale approaches


A PhD position is available at Duke University for a candidate with interest and past experience in the broad area of computational mechanics. Research application areas include topics at the interface of mechanical modeling, scientific computing and materials science, such as stochastic multiscale analysis for engineered or biological systems.

The successful candidate would be funded by an internal grant, with possible applications in a project funded by the National Science Foundation (NSF). The position includes a competitive salary and benefits. The start date is Fall 2018. International applicants are encouraged to anticipate requirements from the Duke Graduate School, and the application must be submitted online (typically, by December 2017).

Nature du financement

Contrat doctoral

Précisions sur le financement

Fellowship from Duke University

Présentation établissement et labo d'accueil

Duke University

Duke University is regularly recognized as one of the best places to work in higher education. In nine of its last 10 surveys, including its most recent survey released in July 2017, The Chronicle of Higher Education listed Duke among its "Great Colleges to Work For." Duke's hometown, Durham, NC, is itself regularly listed among the best places in the United States to live, work, play and raise a family.

Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employee opportunity without regard to an individual's age, color, disability, genetic information, gender, gender identity, national origin, race, religion, sexual orientation, or veteran status.

Profil du candidat

Candidates should have:
- A Master degree with a major in Mechanics or Materials Science, and possibly a minor in Applied Mathematics.
- Demonstrated ability to work collaboratively on cross-disciplinary projects.
- Strong oral and written communication skills.
- Outstanding academic records.

Candidates with training and interest in computational multiscale mechanics, scientific computing and/or uncertainty quantification are particularly encouraged to apply.

Date limite de candidature


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