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Field
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compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand response, transactive energy peer-to-peer trading, and
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Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field observations—including
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interactions. This involves (i) developing predictive machine learning models that forecast user actions and remote system responses across audio, video and haptic modalities, and (ii) jointly orchestrating
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Summary: As a postdoctoral research fellow, this position will be responsible for developing and executing research plans designed in collaboration with a talented team of faculty, postdocs, and graduate
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» Nuclear engineering Engineering » Control engineering Engineering » Mechanical engineering Physics » Electronics Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application
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models that forecast user actions and remote system responses across audio, video and haptic modalities, and (ii) jointly orchestrating network and computing resources to compensate for the gap between
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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
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of the MishMash center Documented experience in computer networks and/or distributed systems is a strong advantage It is an advantage to be knowledgeable in non-AI statistics and mathematical modeling It is an
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political science and be proficient in conducting quantitative analyses. Experience with computational text analysis and large language models is an advantage but not a requirement. Knowledge in comparative
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 3 hours ago
team science model Collaborative approach to research and training Initiative, independence, and integrity Ability to work on sensitive subject matter in a mature manner Departmental Preferred Experience