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solutions, not just infrastructure — someone who sees a research challenge and immediately starts thinking about what combination of agents, models, and pipelines could solve it. Part of the work is carried
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large language model and agentic systems, including multi-agent orchestration frameworks, tool and protocol integration standards, self-hosted and API-based inference, evaluation, and prompt engineering
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that support research and operational workflows across the Office of Data Science. This role will focus on building and orchestrating advanced LLM-based agents, developing secure and interoperable infrastructure
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applications under appropriate data-governance controls. Evaluate model and agent performance for accuracy, reliability, safety, and bias; document results and iterate based on findings. Collaborate with
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agents into gaming scenarios (e.g., gameplay, interactions, procedural content generation, dynamic narratives) Leverage fine-tuned Vision-Language Models (VLMs) for game scenario detection, supporting zero
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which large language models, prompts, and AI agents are used to design and implement computational workflows and to evaluate their assumptions, limitations, uncertainty, bias, implications for authorship
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, KY The Extension Agent for Family and Consumer Sciences will: develop, implement, and evaluate a plan of work based on locally identified needs, which will lead to improved quality of living
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vision, operating model, governance framework, and roadmap for AI-enabled solutions across the institution. This role is responsible for building and leading a high-performing AI engineering organization
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. This role is based within the Faculty of Life Sciences & Medicine, within the School of Immunology & Microbial Science in the Department of Infectious Diseases, which brings together expertise across
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of AI security best practices, including data privacy, model security, and adversarial robustness. Experience designing and delivering cohort-based, multi-tiered, or workforce-focused learning programs