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evaluate new reagents, technologies, and laboratory workflows for comprehensive viral detection. Developing and evaluating molecular approaches including PCR-based sequencing, targeted NGS, pan-viral
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Description about scope of the PhD research: Do you have a background in energy informatics, computer science, or energy systems, and are you are interested in edge intelligence, multi-agent AI, and
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- “Functional skincare and film-forming agent”. Qualifications Applicants should have a doctoral degree or an equivalent qualification and must have no more than five years of post-qualification experience
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databases. Our team studies a range of interventions, from psychotropic agents to vaccines, in relation to multiple outcomes, from pregnancy losses to neurodevelopmental disorders in the infant. We apply
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. Advanced machine learning, reinforcement learning, and agent-based optimization techniques will be developed to reduce voltage deviations, cut active power curtailment, and improve system adaptability under
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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to) • AI4SCI, with an emphasis on atomic systems such as molecules, proteins, and materials • Modern energy/entropy based learning • LLM/Agent for science • Related safety issues in AI4SCI Dr. Bian
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multi-agent frameworks. Familiarity with immersive platform development (e.g., Roblox, Minecraft), including scripting (Lua/Java), agent behavior modeling, event handling, and API-based integration with
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: Under guidance of the mentor, you will assist in determining the host associations of introduced biological control agents with the invasive emerald ash borer (EAB) and other related pests. Part of
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on integrating an agentic platform for electrocatalyst discovery and developing novel machine-learning algorithms (e.g., reinforcement learning) for materials discovery and process optimization. The candidate will