Education STEM OPT Jobs in Virginia
Education F-1 STEM OPT sponsorship jobs in Virginia are concentrated around Northern Virginia's dense cluster of ed-tech firms, research universities, and federal contractors in the K-12 and higher education space. Employers including Stride K12, 2U, and Anthology have filed LCAs for STEM-eligible education roles, with Arlington, Reston, and Fairfax among the most active hiring corridors for international STEM OPT candidates.
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Get Access To All JobsINTRODUCTION
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.
ROLE AND RESPONSIBILITIES
- 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 peer-reviewed 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: 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).
- 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.
- 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
INTRODUCTION
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.
ROLE AND RESPONSIBILITIES
- 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 peer-reviewed 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: 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).
- 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.
- 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
STEM OPT Education Job Roles in Virginia
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Search Education Jobs in VirginiaEducation STEM OPT Sponsorship Jobs in Virginia: Frequently Asked Questions
Which education companies sponsor F-1 STEM OPT visas in Virginia?
Several Virginia-based education employers have filed Labor Condition Applications for roles. Companies such as Stride K12, 2U, Anthology, and Cengage have active operations in Northern Virginia and have historically sponsored international workers in data, engineering, and instructional technology positions. Federal contractors delivering education programs, particularly around the Arlington and Reston corridors, also appear regularly in OFLC disclosure data for STEM OPT-eligible roles.
Which cities in Virginia have the most education F-1 STEM OPT sponsorship jobs?
Northern Virginia dominates F-1 STEM OPT hiring in the education sector. Arlington, Reston, Herndon, and Fairfax concentrate the highest density of ed-tech employers, federal education contractors, and university system offices. Richmond also has opportunities tied to Virginia Commonwealth University and nearby research institutions. Charlottesville sees activity from the University of Virginia's technology and research divisions, which frequently post STEM-eligible roles.
What types of education roles typically qualify for F-1 STEM OPT sponsorship?
F-1 STEM OPT authorization requires your role to appear on the DHS STEM Designated Degree Program List and be directly related to your degree. In Virginia's education sector, qualifying roles commonly include data analyst, software engineer, instructional technology specialist, learning systems developer, and research analyst positions at ed-tech companies or universities. Purely administrative or non-technical teaching roles generally do not qualify. Confirm your specific STEM degree classification with your DSO before accepting an offer.
How do I find education F-1 STEM OPT sponsorship jobs in Virginia?
Migrate Mate filters job listings specifically for employers with verified F-1 STEM OPT sponsorship history in Virginia's education sector, saving you the work of manually reviewing OFLC disclosure files. Search by industry and state to surface ed-tech companies, university employers, and federal education contractors in Northern Virginia and Richmond that have active LCA filings for STEM-eligible roles. Confirming LCA history before applying helps you prioritize employers already familiar with the STEM OPT process.
Are there state-specific considerations for F-1 STEM OPT sponsorship in Virginia's education sector?
Virginia requires all E-Verify enrollment for employers hiring through STEM OPT, and Virginia's large federal contracting presence means many education employers already participate. Northern Virginia's proximity to federal agencies also means some roles may carry security clearance requirements, which can complicate sponsorship timelines for international candidates. Virginia does not impose state-level visa sponsorship restrictions beyond federal requirements, but confirming E-Verify enrollment with each employer before applying is advisable.