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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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ESEM, a FIB system, and a complete suite of sample preparation tools. The role will involve the coordination of day-to-day operations of the unit, ensuring optimal equipment performance, user
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. Evaluate and implement digital tools and platforms that support research activities, data management, and collaboration. Process Optimization: Analyze current workflows across research and administrative
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this short-term project we will use active learning to accelerate the training of deep learning algorithm to optimize 2D material Van der Waals structure discovery. Main Tasks and responsibilities: The person
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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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multidisciplinary environment. PhD Research Focus The selected PhD student will contribute to the design, fabrication, and optimization of electrochemical devices, exploring novel electrode materials, miniaturization
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maintain laboratory equipment, implementing upgrades as needed. The candidate must possess the technical expertise to operate, troubleshoot, and ensure the optimal performance of all instruments through
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and responsibilities: Testing of the microscope's components to assure full functionality. Installation of the system. Adapting the control electronics and software for optimizing user-friendly
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defect engineering in cerium oxide nanoparticles to optimize their redox activity and catalytic properties. This involves aqueous, room-temperature synthesis methods, advanced spectroscopic