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research into control theory of neural population dynamics. This position has the specific focus of developing ML methods to assess the feedback controllability of neural population dynamics recorded from
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or experience in distributed training on large scientific datasets and staying current with new training methods and architectures. Experience with performance and profiling tools such as Perftools, NVIDIA Nsight
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Chemistry, Physics, Materials Science, or a related field. Hands-on experience with first-principles or atomistic methods relevant to interfacial systems, including DFT, ab initio MD, enhanced sampling
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for science Advancing quantum computing and networking technologies, software, algorithms and applications Evaluating or developing new and promising HPC systems and networking technologies Researching methods
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field. Demonstrated ability to perform research that addresses fundamental science questions. Demonstrated experience with computational chemistry methods including density functional theory, molecular