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for massively parallel computers. Experience with quantum many-body methods. Preferred Qualifications: A strong computational science background. Familiarity with coupled-cluster method. Understanding
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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Position Summary Functional Genomics of circular RNAs in Alzheimer's Disease. The Cruchaga Lab, member of the NeuroGenomics and Informatics Center, is recruiting a motivated, creative, self-driven
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software for multi-arch environments Development in high-performance computing (HPC) or distributed systems Strong understanding of Linux toolchains, build systems (CMake), and debugging tools Parallel
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commercial electronic design libraries, combining high-frequency circuit techniques with the constraints of silicon processes. In parallel, you will develop on-chip antenna structures, performing full-wave EM
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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and tool-using agents for experiment design, simulation steering, data collection, and lab/compute orchestration; planning and memory; multi-agent collaboration. Scientific Reasoning: Program/path