Employment

The Health, Education, AI, and Learning (HEAL) Division of the Virginia Modeling Analysis and Simulation (VMASC) and the
National Center for Collaboration in Medical Modeling and Simulation (NCCMMS) is seeking a highly motivated and creative
Postdoctoral Researcher to conduct foundational and applied research in artificial intelligence, deep learning, and advanced neural
network architectures. You will join a multidisciplinary team of computer scientists, engineers, human factors experts, instructional
designers, and medical education experts to design novel algorithms, build scalable training pipelines, and apply cutting-edge machine
learning models to complex, real-world challenges and in pursuit of commercially viable products.

Algorithm Development: Design, implement, and evaluate novel deep learning architectures,
neural surrogate models, or brain-inspired computing algorithms.

Experimentation & Scaling: Plan rigorous, reproducible training evaluations, ablation studies,
and GPU-accelerated experiments across small & large datasets.

Software Engineering: Develop, test, document, and maintain robust, open-source Python
research software using modern version control workflows (e.g., Git).

Publication & Dissemination: Write and collaborate on high-impact research articles for peerreviewed
journals and present findings at premier international AI/ML conferences (e.g.,
NeurIPS, ICML, ICLR).

Collaboration & Mentorship: Collaborate effectively within interdisciplinary/transdisciplinary
research groups and assist in mentoring junior graduate or undergraduate researchers.

Minimum Qualifications:

Education and/or training:
 Education: Ph.D. in Computer Science, Artificial Intelligence, Applied Mathematics, Data Science, Computational
Physics, Electrical & Computer Engineering, or a closely related quantitative field (conferred by December 2026 and
within the past 5 years).
Level and type of experience
 Technical Expertise: Demonstrated research experience in human-computer interaction, machine learning, and deep
learning. Solid technical foundation in development and evaluation of supervised, unsupervised, and/or reinforcement
learning models. Experience with discriminative and generative models.
Specific knowledge, skills, and abilities:
 Programming Skills: Strong programming proficiency in Python and hands-on experience with modern deep learning
frameworks such as TensorFlow, PyTorch, or JAX.

Preferred qualifications:

 Experience working with multimodal neural network development, including video recordings, audio transcripts, and
associated digital human performance scores, is desired.
 Experience with specialized architectures (GPUs, TPUs).
 Background in physics-informed neural networks (PINNs), foundation models, world models, or uncertainty
quantification.
 Special Experience with high-performance computing (HPC) environments and distributed training workflows.

This position is being filled through the Research Foundation, which is a separate entity from Old Dominion University (ODU). While we work in support of ODU, the Research Foundation operates independently and is a not-for-profit, tax-exempt 501(c)(3) organization.

To apply: click Job Browsing; and follow the link for position #26-058.  Review of applications will begin immediately and will continue until the position is filled

The organization is an equal opportunity and affirmative action employer (AA/EOE/M/F/Disability/VETS/Drug-Free Workplace). We are committed to providing equal employment opportunity to all individuals in accordance with applicable federal, state, and local laws. Employment decisions — including recruitment, hiring, training, compensation, and promotion — are made without regard to race, color, religion, sex, national origin, physical or mental disability, genetic information, age, protected veteran status, or any other protected characteristic. Affirmative action efforts are conducted consistent with applicable laws to promote equal opportunity in employment and advancement.

As part of our commitment to pay transparency and compliance with applicable laws, the Research Foundation includes a good-faith salary range in all job postings. These ranges represent the expected hiring range for the position, not the full compensation band.

Final salary offers may vary depending on factors such as experience, qualifications, skills, internal equity, and budget availability.

Expected Salary Range:  $55,000 to $65,000