Sort by
Refine Your Search
-
optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
-
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
-
, 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
-
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
-
-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
-
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
-
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
-
: 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
-
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
-
of such scientific objectives. The person in charge of scientific direction will evaluate the scientific proposals of the different CNIO Programs and will propose as many actions as necessary for the optimal execution