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Mathematical Modeling Postdoc Jobs in Virginia (NOW HIRING)

... of Mathematics at Virginia Tech, Blacksburg, VA. The postdoctoral fellow will work under the supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The ...

D. in civil and environmental engineering, mechanical engineering, applied mathematics, physics ... modeling of subsurface systems, including fluid diffusion, stress evolution, and fault or fracture ...

... Statistics, Mathematics, Biophysics, Physics, Chemistry, Biology or related fields. PhD must be ... Published research experience in AI for scientific discovery and/or AI-driven biomolecular modeling ...

Postdoctoral Associate Apply now Back to search results Job no: 536557 Work type: Research Faculty ... mathematical or computational modeling background Evidence of peer-reviewed publications in ...

The candidate will apply a suite of statistical and physical models for integrating observations of ... D. in Earth Sciences, Geodesy, Physics, Mathematics, Computer Sciences, Civil & Environmental ...

The Research Scientist will join the Coastal Systems Modeling Group within CCRM to support and ... Work closely with graduate students, postdoctoral associates, and visiting scientists * Participate ...

Mathematical Modeling Postdoc information

What is the difference between Mathematical Modeling Postdoc vs Data Scientist?

AspectMathematical Modeling PostdocData Scientist
Required CredentialsPhD in Mathematics, Applied Mathematics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; PhD preferred
Work EnvironmentAcademic research institutions, universities, research labsCorporate, tech companies, startups, or consulting firms
Industry UsageResearch projects, academic publications, grant-funded studiesBusiness analytics, product development, data-driven decision making
Common Search & ComparisonYesYes

While both roles involve analytical skills and data handling, Mathematical Modeling Postdocs focus on academic research and developing theoretical models, whereas Data Scientists apply data analysis techniques to solve practical business problems. The choice depends on whether you prefer research-oriented work or industry applications.

What does a Mathematical Modeling Postdoc do?

A Mathematical Modeling Postdoc conducts advanced research using mathematical techniques to analyze and solve complex real-world problems in fields such as biology, engineering, physics, or social sciences. They typically develop and apply mathematical models, run simulations, analyze data, and interpret results to support scientific or industrial projects. Postdocs in this role often collaborate with interdisciplinary teams, publish research findings, and may also assist in mentoring students or contributing to grant proposals.

What are some common challenges faced by Mathematical Modeling Postdocs when transitioning from academic research to collaborative industry projects?

Mathematical Modeling Postdocs often encounter challenges when moving from academic research to industry settings, particularly in adapting to faster-paced timelines and working within interdisciplinary teams. In industry, projects may require quick prototyping and the ability to communicate complex mathematical concepts to non-experts, such as engineers or business stakeholders. Building effective collaborations and aligning research goals with organizational objectives can also be a significant adjustment. However, these challenges provide valuable experience and broaden career prospects in both academia and industry.

What are the key skills and qualifications needed to thrive as a Mathematical Modeling Postdoc, and why are they important?

A Mathematical Modeling Postdoc requires an advanced degree (typically a PhD) in mathematics, applied mathematics, or a related quantitative field, along with strong analytical and problem-solving abilities. Expertise with programming languages such as Python, MATLAB, or R, and experience with simulation software or computational tools, are commonly expected. Strong communication, collaboration, and critical thinking skills help in presenting findings and working effectively within research teams. These competencies are vital for developing robust models, interpreting complex data, and contributing to innovative research outcomes.
Postdoctoral Associate

Full-time

Posted 17 days ago


Virginia Tech rating

7.7

Company rating: 7.7 out of 10

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Job description

Postdoctoral Associate
Job no: 534113
Work type: Research Faculty
Senior management: College of Science
Department: Mathematics
Location: Blacksburg, Virginia
Categories: Instructional / Teaching Faculty, Research / Scientific
Job Description
Applications are invited for one Postdoctoral Associate position with the Department of
Mathematics at Virginia Tech, Blacksburg, VA. The postdoctoral fellow will work under the supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order models and machine learning techniques for kinetic equations arising from plasma and neutron transport.
The position will be based at Virginia Tech's campus in Blacksburg, VA. The postdoc will have a teaching load of 2 classes per year. The position is for two years, and can be renewed for a third year pending satisfactory performance.
Required Qualifications
• 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.
• 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 with the scientific computing library and parallel programming.
• Experience with writing scientific articles.
• Experience with writing scientific machine learning.
Overtime Status
Exempt: Not eligible for overtime
Appointment Type
Restricted
Salary Information
Commensurate with experience
Hours per week
40 hours - exempt position
Review Date
December 1, 2025
Additional Information
The successful candidate will be required to have a criminal conviction check.
About Virginia Tech
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 Blacksburg, the greater Washington, D.C. area, the Health Sciences and Technology Campus in Roanoke, sites in Newport News and Richmond, and numerous Extension offices and research institutes. A leading global research institution, Virginia Tech conducts more than $650 million in research annually.
Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance. These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.
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, ethnicity or 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 sworl9@vt.edu during regular business hours at least 10 business days prior to the event.
Advertised: February 23, 2026
Applications close:
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About Virginia Tech

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Virginia Tech, guided by its motto "Ut Prosim" (That I May Serve), embraces a hands-on, interdisciplinary approach to educate scholars as leaders and problem-solvers. As a comprehensive land-grant institution, it enriches the quality of life in Virginia and worldwide, fostering an inclusive community focused on knowledge, discovery, and creativity. With over 280 majors, the university serves a diverse student body of more than 36,000 across undergraduate, graduate, and professional programs. Virginia Tech's presence extends throughout Virginia, including campuses in Northern Virginia, Roanoke, Newport News, and Richmond, along with multiple Extension offices and research centers. As a prominent global research institution, it conducts over $500 million in research annually.

Industry

Colleges, universities, and professional schools

Company size

5,001 - 10,000 Employees

Headquarters location

Blacksburg, VA, US

Year founded

1872

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