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for government, industry and the public. The research will focus on: Agentic AI systems and their governance Physical AI and its integration with real-world systems Measurement and evaluation of agentic AI
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-pathogenic bacterial infectious agents in the context of pathogen-host interactions. Expertise in experimental infection and colonization models is desirable. The successful candidate is expected to actively
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department is responsible for education programs in software engineering from Bachelor to Ph.D. levels. Work description As a doctoral student in this position, you are expected to explore how AI agents
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methylation patterns, and histone modifications, to determine the safety of CK2II as a potential fertility preservation agent. De novo mutations will be analyzed in both oocytes and somatic cells, while genome
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
the School’s Strategic Plan (https://pharmacy.unc.edu/about/oe/strategic-plan/). Our Vision is to be the global leader in pharmacy and pharmaceutical sciences. Our Mission is to prepare leaders and innovators
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
and World Report. The School has experienced unprecedented growth and success and continues to strategically position itself for sustained impact, as articulated in the School’s Strategic Plan (https
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Posting Details Posting Details Job Title Extension Agent for Horticulture – Kenton County Requisition Number RE54643 Working Title Department Name 81C08: KCES Region Central Area 08 Work Location
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https://www.ubjobs.buffalo.edu/postings/63831 Employer Research Foundation Position Type RF Clerical/Technical Job Type Full-Time Appointment Term Salary Grade N.4 Posting Detail Information Position
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(Terraform or CloudFormation) 2 years of the six years to include experience with data engineering practices incorporating AI capabilities, including: Proven success leveraging generative AI, agent-based
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-based reasoning strategies for oncology, including tool-augmented inference, multi-agent or compound model workflows, process supervision, verifier-guided training, and reinforcement learning-based post