The Bradley Department of Electrical and Computer Engineering (ECE) at Virginia Tech invites applications for multiple Postdoctoral Associate positions in trustworthy artificial intelligence (AI). The successful candidates will conduct research aimed at making the decisions and behavior of AI models and agents more transparent, interpretable to humans, safe, and reliable. Research may include developing methods to understand and explain AI decision-making; identifying, evaluating, and mitigating potential failures, vulnerabilities, or risks; and improving the robustness and reliability of AI systems in real-world settings.

Working with the faculty supervisor and collaborating researchers, each Postdoctoral Associate will design and execute research studies, disseminate results through peer-reviewed publications and presentations, and develop open-source software, datasets, benchmarks, models, or other research artifacts that benefit the broader research community. The position will also contribute to the development of research proposals and mentor undergraduate students participating in related projects. The appointments provide opportunities for interdisciplinary collaboration and professional development in preparation for careers in academia, industry, government, or the nonprofit sector.

• Ph.D. in computer science, electrical or computer engineering, data science, statistics, applied mathematics, or a closely related field completed by the appointment start date.
• PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
• Record of research in artificial intelligence, machine learning, or a closely related area, documented through the curriculum vitae, resume, cover letter, doctoral dissertation, publications, preprints, or other research products identified in the application materials.
• Record of designing and conducting computational or empirical research, including research methodology, implementation, analysis, or documentation, as reflected in research projects, publications, dissertation work, or other scholarly products identified in the application materials.
• Programming proficiency relevant to AI or machine-learning research, evidenced by research code, software projects, technical portfolios, repositories, publications, or equivalent work products identified in the application materials.
• Record of written and oral technical communication, evidenced by publications, dissertation work, technical reports, conference or seminar presentations, teaching materials, or other examples identified in the application materials.
• Record of contributing to both independently led and collaborative research, software, publication, or technical projects, as documented in the curriculum vitae, resume, cover letter, or other application materials.

• Research expertise in one or more areas related to trustworthy AI, such as explainable or interpretable AI, AI safety, robustness, reliability, uncertainty quantification, model evaluation, fairness, privacy, security, human-AI interaction, or the evaluation and alignment of AI agents.
• Experience with contemporary AI systems, including deep learning, foundation models, large language models, multimodal models, reinforcement learning, or agentic AI systems.
• Record of publication in peer-reviewed journals or selective conferences relevant to artificial intelligence, machine learning, human-computer interaction, cybersecurity, or related fields.
• Experience developing and maintaining open-source research software, reproducible workflows, datasets, benchmarks, model evaluations, or other community-facing research artifacts.
• Experience contributing technical content to grant proposals, sponsored-research reports, or collaborative research plans.
• Experience mentoring or supervising undergraduate or graduate researchers.
• Experience evaluating AI systems in applied or real-world settings, including work with interdisciplinary collaborators or external partners.

Exempt: Not eligible for overtime

Restricted

$63,480 – $68,480, Commensurate with Experience

40

November 2, 2026

The successful candidate will be required to have a criminal conviction check.

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.