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the supervision of Dr. Jun Xu Develop high-quality models, algorithms, experiments, or integrated modeling-characterization frameworks Publish first-author papers in leading peer-reviewed journals Contribute
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intelligence. This part focuses on robotic agents operating in unstructured 3D environments (homes, offices, industrial sites, shopping malls). The work centres on (a) model-based and hybrid RL algorithms built
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, investigate new algorithms and architectures, and work closely with hardware and system research teams to advance the state of the art in next-generation communication systems. You are expected to publish
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We are seeking a part-time Research Assistant in computer vision and machine learning for human behavior analysis and modeling. The successful candidate will investigate new algorithms and models
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Fellow to conduct cutting-edge research in high-resolution electromagnetic imaging and intelligent sensing. The successful candidate will contribute to the theoretical development, algorithm design, and
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algorithm design skills Expertise on ML tools for chemistry, in particular, generative AI Experience with Python, ML, and AI for chemical applications Job Description: A Post-doctoral Associate in Theoretical
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research and implementation. You will also develop novel algorithms using state-of-the-art computer vision and machine learning techniques (segmentation, multimodal AI, foundation models, agentic frameworks
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). - Quantum algorithm design. - Error correction or error mitigation. Certifications/Licenses Required Knowledge, Skills, and Abilities Strong background in quantum chemistry, computational physics
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control algorithms. Perform experimental testing, data analysis, and performance evaluation of power electronic systems. Develop simulation models using tools such as MATLAB/Simulink, PLECS, or PSCAD
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Health, powered by the All of Us Research Program is a new initiative to develop algorithms that predict individual responses to food and dietary patterns. The NPH Consortium consists of 12 awardees across