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managing distributed assets, market participation, and social acceptance. The main research objectives of this project are to: Develop AI-based models for multi-objective portfolio optimization or multi
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settings and (ii) explicit task execution knowledge embedded in multi-modal documents. This research will specifically look at the development of embodied and embedded intelligence, which allows AI-based
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vehicle validation. Design and implement machine learning models that capture the complexity and variability of real-world traffic situations, including unusual pedestrian behaviors, edge cases, and multi
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generation ● Experience with retrieval-augmented generation, agentic or multi-stage workflows, or knowledge-integrated models ● A strong publication record in top-tier AI/NLP venues (ACL, EMNLP
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
for the Environment (IE) has a multifaceted mission: (1) To strengthen environmental research capacity across UNC by supporting a multi-disciplinary community of scholars that enhances collaboration, increases sharing
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to treat advanced prostate cancer including treatments that exploit androgen receptor signaling, DNA repair deficiency and immune-based agents. We are recruiting a post-doctoral fellow to engage in
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or adaptive systems reinforcement learning, multi-agent systems, network or graph-based models simulation of complex socio-technical or organisational systems causal inference, econometric analysis, or formal
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responses to different investigated factors (stresses, amendment, photoperiod, etc.) Develop and deliver training modules to farmer’s, cooperatives, extension agents, etc. Data scheduling, collection