Virginia Tech, Mathematics

Position ID: VirginiaTech-PA_DA [#23245]
Position Title: Postdoctoral Associate
Position Type: Postdoctoral
Position Location: Blacksburg, Virginia 24061, United States [map] sort by distance
Application Deadline: 2024/01/02 11:59PMhelp popup (posted 2023/09/28)
Position Description:    

*** the listing date or deadline for this position has passed. ***

Postdoctoral Associate

Applications are invited for at least one Postdoctoral Associate position with the Department of Mathematics at Virginia Tech, Blacksburg, VA. The postdoctoral fellow will work under the supervision of Prof. Daniel Appelö on modeling and numerical methods for linear and non-linear wave phenomena. Examples of such applications will come from computational electromagnetics, acoustics, seismology and modeling of quantum computers. The research conducted will involve development and analysis of fast large-scale solvers based on traditional techniques (element based or nodal based methods) and up-and-coming techniques (scientific machine learning). We have interest in forward and inverse problems in both the deterministic and stochastic setting.

The positions will be based at Virginia Tech’s campus in Blacksburg, VA. The postdoc will have a teaching load of 1 to 2 classes per year. The positions are for two years, and can be renewed on the third year pending satisfactory performance.

Required Qualifications: ● We seek candidates with a PhD in Mathematics or an equivalent area, and with a strong background in numerical analysis and scientific computing. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining. ● Strong background in the development and/or application of numerical methods for partial differential equations. ● Experience in implementation of numerical methods in C/C++, Fortran, Julia, Python. ● Interest and experience in at least one application from the areas mentioned above. ● Ability to work with others in an interdisciplinary environment.

Preferred Qualifications: ● Experience in scientific machine learning. ● Experience with the scientific computing library and parallel programming. ● Experience with writing scientific articles with LaTeX.

An online application is required. To apply, please visit, select "Apply Now" and search by posting number 527146. For full consideration submit a cover letter, a CV, a research statement, and a teaching statement as part of the online application no later than January 2, 2024. Each applicant should follow the instructions in the online application system to request that three references submit letters of recommendation. This will prompt the system to request submission of recommendation letters. Reference providers should submit their letters by January 2, 2024. Additional information about position requirements and responsibilities can be found at or The faculty handbook (available at provides an overview of faculty appointments.

The successful candidate will be required to have a criminal conviction check.

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

About Virginia Tech

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire an accommodation, please contact Sarah McDearis at during regular business hours at least 10 business days prior to the event.

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Contact: Sarah McDearis, 540-231-3059
Email: email address
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Department of Mathematics
Virginia Tech
225 Stanger Street
460 McBryde Hall
Blacksburg, VA 24061
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