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extensive experience in the application of molecular dynamics simulations to molecular systems, ideally in both methods and applications. Experience in biomolecular simulations particularly nucleic acid
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computational methods for the control, optimization, and coordination of complex dynamical systems. The work will emphasize applications to multi-agent systems, including robotics, autonomous systems, and
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scientific research uses computer vision to pioneer new methods for 3D cellular structure analysis and cryo-electron tomography (cryo-ET). Dr. Qirong Ho – Assistant Professor of Machine Learning and Computer
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-efficiency to realized efficient Embodied/Edge-AI implementations. A key focus will be on investigating novel methods with strong theoretical foundations as well as their full-system deployment in real-world
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techniques such as metadynamics, UFED, path sampling, milestoning methods; machine learning applications in chemistry and biophysics, good computer programming skills, and working knowledge of UNIX, phyton
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custom experimental systems. These instruments may combine optical components, laser and spectroscopic methods, spin-control or magnetic-resonance techniques, electronics, data-acquisition hardware, and
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results of the state-of-the-art (SOTA) methods; Design and develop experimental facilities to allow implementing experiments on real platforms operating indoors and outdoors, to compare our proposed work
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on investigating novel methods with strong theoretical foundations as well as their full-system deployment in real-world applications from different fields (like autonomous systems, healthcare, and robotics) with