Postdoctoral Associate - Trustworthy Artificial Intelligence
About The Position
The Bradley Department of Electrical and Computer Engineering at Virginia Tech is hiring multiple Postdoctoral Associates to conduct research in trustworthy artificial intelligence. The research aims to make AI model and agent decisions and behavior more transparent, interpretable to humans, safe, and reliable. Potential areas include explaining AI decision-making, identifying and mitigating failures, vulnerabilities, and risks, and improving the robustness and reliability of AI systems in real-world settings. In collaboration with a faculty supervisor and other researchers, each Postdoctoral Associate will design and conduct research studies; publish and present findings; develop open-source software, datasets, benchmarks, models, and other research artifacts; contribute to research proposals; and mentor undergraduate students on related projects. The appointments offer interdisciplinary collaboration and professional development for careers in academia, industry, government, or the nonprofit sector.
Requirements
- 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.
- Ph.D. must have been awarded no more than four years before the effective appointment date, with at least one year of eligibility remaining.
- Record of research in artificial intelligence, machine learning, or a closely related area.
- Record of designing and conducting computational or empirical research, including research methodology, implementation, analysis, or documentation.
- Programming proficiency relevant to AI or machine-learning research.
- Record of written and oral technical communication.
- Record of contributing to independently led and collaborative research, software, publication, or technical projects.
Nice To Haves
- Research expertise in one or more trustworthy AI areas, such as explainable or interpretable AI, AI safety, robustness, reliability, uncertainty quantification, model evaluation, fairness, privacy, security, human-AI interaction, or AI-agent evaluation and alignment.
- Experience with contemporary AI systems, including deep learning, foundation models, large language models, multimodal models, reinforcement learning, or agentic AI systems.
- Peer-reviewed publication record in journals or selective conferences relevant to AI, 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.
Responsibilities
- Design and execute research studies in trustworthy artificial intelligence.
- Work with a faculty supervisor and collaborating researchers.
- Conduct research to improve the transparency, interpretability, safety, and reliability of AI models and agents.
- Disseminate research results through peer-reviewed publications and presentations.
- Develop open-source software, datasets, benchmarks, models, and other research artifacts for the broader research community.
- Contribute to the development of research proposals.
- Mentor undergraduate students participating in related projects.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
