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AI Research Facilitator

Job in Athens, Clarke County, Georgia, 30602, USA
Listing for: The University Of Georgia
Full Time position
Listed on 2026-07-01
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Data Scientist, AI Business & Operations, Machine Learning/ ML Engineer
Job Description & How to Apply Below

AI Research Facilitator

The Georgia Advanced Computing Resource Center (GACRC), a division of Enterprise Information Technology Services at the University of Georgia, seeks to establish an AI Research Facilitator position to support the University's rapidly expanding needs in artificial intelligence and data-driven research. The GACRC provides advanced computing and research storage services to more than 500 research groups, and recent multimillion-dollar investments in GPU-accelerated infrastructure have positioned UGA to support leading-edge AI research across disciplines.

Over the past three years, the University has undertaken the Presidential Interdisciplinary Faculty Hiring Initiative in Data Science and Artificial Intelligence, bringing approximately 70 new faculty hires to campus. At the same time, existing faculty across the sciences, social sciences, humanities, arts, and professional programs are increasingly incorporating AI and machine learning into their research portfolios. To fully realize the potential of these rapidly growing AI-driven initiatives, UGA must provide specialized, human-centered research support that complements its advanced computing investments.

The AI Research Facilitator will play a central role in enabling faculty to effectively leverage AI methodologies, accelerating research impact across the institution.

Knowledge, Skills, Abilities and/or Competencies
- Demonstrated expertise using modern AI/ML frameworks (e.g., PyTorch, Tensor Flow, Scikit-learn). Deep understanding of large language models (LLMs), including model architectures, training and fine-tuning approaches, inference pipelines, and responsible use in research contexts. Proficiency in Python, R, CUDA, or other languages common in AI research. Experience working with GPU-accelerated computing resources, preferably within an HPC environment. Experience preparing, managing, and curating datasets for machine learning workflows.

Ability to translate faculty research goals into appropriate AI methods, models, and computational strategies. Working knowledge of ethical AI principles, bias mitigation, and reproducibility practices. Strong communication skills, including experience developing workshops, training materials, or documentation for varied audiences. Demonstrated ability to work effectively in collaborative, interdisciplinary research environments.

Duties/Responsibilities - AI Research Support and Consultation Provide hands-on consultation to faculty and graduate students integrating AI, machine learning, or data-intensive methods into their research workflows. Assist with data preparation, model development, training optimization, and performance tuning on GPU-accelerated systems. Offer tailored, high-engagement guidance to new AI-focused faculty as well as existing researchers expanding into AI-driven approaches.

Duties/Responsibilities
- Training, Outreach, and Community Building Develop workshops, online training modules, and documentation to broaden AI skills and best practices across campus. Support interdisciplinary collaborations by connecting researchers with shared computational approaches. Engage departments adopting AI for the first time to ensure sustainable and responsible integration of AI tools into research and teaching.

Duties/Responsibilities
- Coordination and Institutional Alignment Work closely with GACRC and EITS leadership, the Office of Research, the Institute for AI, and academic units to ensure services align with evolving research needs. Provide input to help guide institutional strategy for AI computing, workflows, and research support.

Duties/Responsibilities
- Technology Monitoring and Evaluation Stay current with emerging AI frameworks, workflows, tools, and best practices. Assess new technologies and their potential to improve research productivity or strengthen UGA's AI research capabilities.

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