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Field
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-VLMs, tiny-VLAs; Agentic-AI systems; and Robust Generative AI targeting hallucination, safety and security issues. Besides robustness, systems should also be optimized for high performance and energy
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be optimized to maintain low resistance and efficient packing of active electrode materials. These printed batteries will be designed to provide a stable cell-level capacity of at least 2 mAh in a coin
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molecular and cellular techniques such as gene cloning, PCR, western blotting, transfection and transduction, drug treatment, cell culture, flow cytometry and cell sorting. Experiences in handling mice and
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, optimization, and characterization integrating imaging, experimental metadata, and diffraction outcomes. Design and deploy computer vision methods to detect and track crystal growth. Develop closed-loop
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 13 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 | 13 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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lasting impact on national, continental, and global scales, positioning itself as a leader in education, research, and innovation. The Materials Science, Energy, and Nano-engineering (MSN) department
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Experimental High Energy Physics beginning no sooner than August 1st, 2025. The successful candidate will join the Experimental High Energy Physics group led by Profs. Brinkerhoff, Dittmann, Hatakeyama, and
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position within a Research Infrastructure? No Offer Description Activities: Post-Doctoral position #1 – HTT Pilot Plant Operation and Technology Scale-up: Lead the operation, optimization, and technology
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Do you want to contribute to the future of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware