Postdoctoral Associate

About the Role

The Virginia Tech National Security Institute (VTNSI) seeks a Postdoctoral Associate to conduct research in computational modeling and uncertainty quantification within a multidisciplinary program.

Key Responsibilities

• Develop surrogate models of computational systems using reduced-order and machine learning approaches.
• Leverage Bayesian and other methods for parameter estimation, uncertainty quantification, and recommending new points for training or full-order model evaluation.
• Contribute to the preparation of peer-reviewed publications and scientific presentations.
• Assist in mentoring students involved in related research activities.
• Participate in collaborations and travel to conferences.
• Contribute to an NIH-funded research project focused on women’s health outcomes by investigating hormonal influences on vaginal tissue structure and function.
• Collaborate with researchers in Mathematics and Mechanical Engineering at Virginia Tech and other institutions.

Requirements & Tech Stack

• Ph.D. in Applied Mathematics, Computational Science, Mechanical Engineering, Aerospace Engineering, Engineering Mechanics, or a closely related field. PhD must be awarded no more than four years prior to appointment with a minimum of one year eligibility remaining.
• US Citizen (due to sensitivity of institute work).
• Demonstrated experience in Bayesian inference, parameter estimation, and uncertainty quantification.
• Demonstrated experience with computational modeling of physical or engineering systems.
• Experience with scientific programming using Python, MATLAB, Julia, C/C++, or similar computational tools.
• Demonstrated record of scholarly research, including peer-reviewed publications.
• This position is located in Blacksburg, VA.
• A criminal conviction check will be required.

Qualifications

• Experience building and training artificial intelligence and machine learning models.
• Experience with common machine learning software packages such as PyTorch, Hugging Face, Jax, etc.
• Experience with active learning or Bayesian optimization.
• Experience with surrogate modeling of physical systems.
• Ability to work independently and take ownership of research activities.
• Ability to contribute effectively to collaborative research.
• Ability to work effectively with undergraduate and graduate students and contribute to their research training and mentoring.