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Vision, MBZUAI & Associate Professor, Carnegie Mellon University. Dr. Xu directs a dynamic research laboratory focused on computational biology, bioimage informatics, and structural biology. His core
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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
to applicants with expertise in machine learning, wave propagation, metamaterials, and/or fluid–structure interactions. Applicants must hold a Ph.D. in Mechanical Engineering or a closely related discipline, with
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Quantum Science. The successful candidate will pursue research spanning quantum optics, spin-based systems, and the design and construction of advanced experimental instruments. Applicants with a strong
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Science Instrumentation. The successful candidate will join the Quantum center and will focus primarily on the design, construction, and deployment of advanced instruments for quantum-optical and spin-based
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to provide such descriptions, and uncovering new geometric and topological structures arising from physical phenomena in high energy physics and in condensed matter physics. The successful candidate will be
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theories, with the development of the mathematical constructions that are needed to provide such descriptions, and uncovering new geometric and topological structures arising from physical phenomena in high
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infrastructure inspection and vibration monitoring Successful candidates must hold a PhD degree in Civil, Structural, Mechanical, or Material Engineering. Other related field such as Computer Science, Nuclear
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structure determination using electron or X-ray crystallography. Candidates must have substantial experience in crystallography, specifically in the structure solution and refinement of small molecule
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the areas of Artificial Intelligence (AI) for materials science, with an emphasis on structure-property-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates
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underlying mental processing speed. The successful applicant will drive a fascinating project that links processing speed measures to previously acquired functional and structural MRI data. The project will