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optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
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dynamic, uncertain worlds. Multi-Objective & Black-Box Optimization: Real-world problems rarely have a single, simple objective. We research methods to navigate complex trade-offs (e.g., performance vs
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, construction, and operation of optimized stellarators and other superconducting fusion devices. Candidates at all career stages, from Assistant Professor to Chair Professor and from junior to senior Researchers
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methods to accelerate the discovery and optimization of novel materials, and actively develop large-scale materials models (AI for Science) to transform the R&D process through AI-driven paradigms. In
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-driven AI approaches, we strive to deliver the cost-optimized solutions for development of materials with ultrahigh-temperature stability, high specific strength and structure-function integration through
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tissue engineering, including endothelial cells, smooth muscle cells, and stem cells. Design/Test novel 3D systems: Design and optimize 3D systems to mimic the physiological environment of blood vessels
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expertise and training to its users. Core Responsibilities: 1) Ensure optimal performance and reliability of core facility equipment through proactive maintenance planning. 2) Coordinate full-cycle
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： Recruit and cultivate outstanding researchers and young talents in the field, optimize the structure of research teams, and build internationally recognized scientific teams. Lead teams to conduct high
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Biosafety Level 3 laboratory and houses a national drug clinical trial institution. The school's research platforms are available 24/7 to assist in optimizing experimental plans and achieving innovative and