Summary
The ASTRO Lab in the Department of Mechanical Engineering at Virginia Tech is seeking a Postdoctoral Associate to conduct research in uncertainty quantification and data-driven modeling. This multidisciplinary role involves developing and implementing advanced modeling methods, integrating them with existing finite element and machine-learning models, and contributing to model validation and predictive modeling efforts. The successful candidate will work collaboratively with faculty, researchers, and students, and contribute to publications and presentations.
Designation
Postdoctoral Associate
Research Area
- Uncertainty Quantification
- Data-Driven Modeling
- Bayesian Inference
- Multi-fidelity Modeling
- Reduced-Order Modeling
- Machine Learning for Scientific Computing
- Finite Element Analysis
- Constitutive Modeling
Location
Blacksburg, Virginia, United States
Eligibility/Qualification
Required Qualifications
- Ph.D. in Mechanical Engineering, Aerospace Engineering, Engineering Mechanics, Computational Science, Applied Mathematics, or a closely related field. The PhD must have been awarded no more than four years prior to the effective date of appointment, with a minimum of one year eligibility remaining.
- Demonstrated experience in uncertainty quantification, Bayesian inference, or computational modeling of physical or engineering systems.
- Experience with scientific programming using Python, MATLAB, C/C++, or similar computational tools.
- Demonstrated record of scholarly research, including peer-reviewed publications.
Preferred Qualifications
- Strong scientific writing skills and ability to communicate research findings clearly and effectively.
- Strong oral presentation skills, with experience presenting research to scientific or technical audiences.
- Ability to work independently, take ownership of research activities, and contribute effectively to collaborative research.
- Ability to work effectively with undergraduate and graduate students and contribute to their research training and mentoring.
- Strong organizational, analytical, and interpersonal skills.
- Experience in one or more of the following areas: multi-fidelity or surrogate modeling, sensitivity and identifiability analysis, reduced-order modeling, machine learning for scientific computing, finite element analysis, or constitutive modeling.
- Experience developing and validating computational models.
- Experience with model calibration under sparse or heterogeneous data.
- Experience preparing manuscripts for publication in peer-reviewed journals.
- Experience presenting research at scientific conferences or professional meetings.
- Previous experience mentoring or supervising undergraduate or graduate researchers.
- Demonstrated ability to collaborate effectively across disciplines.
Job Description
The Postdoctoral Associate will be responsible for conducting research in uncertainty quantification and data-driven modeling within a multidisciplinary research program. Key responsibilities include:
- Developing and implementing uncertainty quantification, Bayesian inference, multi-fidelity, and reduced-order modeling methods.
- Integrating these advanced methods with finite element and machine-learning models.
- Contributing to model validation and predictive modeling efforts.
- Collaborating effectively with faculty, other postdoctoral researchers, and graduate and undergraduate students.
- Contributing to the preparation of peer-reviewed publications and scientific presentations.
- Assisting in mentoring students involved in related research activities.
How to Apply
Applicants are encouraged to apply through the official Virginia Tech job portal.
Last Date for Apply
Review Date: October 1, 2026
Apply Link
Apply for Postdoctoral Associate at Virginia Tech
