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AI and Trustworthy AI. • Knowledge Representation and Semantic Technologies. • Multi-Agent Systems and Intelligent Decision Support Systems. • Digital Twins and Smart Water Systems
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) that focus on assessing information processing strategies and corresponding brain function with a single-dose study agent. Primary data collection assessments include MRI scanning (first chair) and EEG
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excellence; and promoting the financial health of the University. More about FAD: Within and across the University, we aim to be exemplary colleagues, trusted partners, valued advisors, and agents of positive
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into different stages of optimization, both as priors and as feedback after optimization outcomes. Information This PhD project is a part of the CoRDS project – Confident Data-Driven Decision Support (https
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R260091 Posting Link https://www.ubjobs.buffalo.edu/postings/63029 Employer Research Foundation Position Type RF Clerical/Technical Job Type Varies Appointment Term Salary Grade N.11 Posting Detail
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privacy of AI systems and AI safety, adversarial machine learning, model and data privacy, secure AI deployment, LLM and agent security, and AI safety, contributing to high-impact research outcomes and the
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deliver high-quality, accurate, and timely admissions services while providing excellent customer support to applicants, University staff, agents, and offshore partners. The role requires strong attention
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the work unit. Know and follow safety procedures and policies in everyday work. Use protective equipment. Scrub and sanitize restrooms, shower rooms and locker areas, using approved cleaning agents and
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of Parkinson’s Disease, identifying therapeutic targets and testing new therapeutic agents. Student Assistant will work in a new lab as part of a highly integrated research team utilizing a variety of laboratory
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven