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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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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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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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areas of nanoscience and nanotechnology. Job Title: PhD student - Inorganic Nanoparticles Group Research area or group: Inorganic Nanoparticles Group Description of Group/Project: The Inorganic
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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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-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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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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of transferred layers will be characterized by Raman. In a second step, the candidate will participate in the optimization of the device parameters (electrode material, geometry, dielectric...) Requirements: PhD
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to design and characterize optimized superconducting microwave resonators tailored for hybrid quantum experiments. · Perform precision measurements in dilution refrigerators at ICN2 and/or MIT, probing
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500 people, including researchers, PhD students and staff personnel. In its area of specialization and category, the institute is consistently ranked among the highest-quality research institutions