21 high-performance-quantum-computing Postdoctoral positions at King Abdullah University of Science and Technology
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genomics, protein engineering, cloning/assembly workflows, cell line development). You will work closely with computational experts to establish innovative, high-throughput, high-fidelity screening platforms
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of selected elements from the cathode materials. System level performance optimization of metal recovery processes. Publish research findings in high-impact journals and present at international conferences
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applications and other emerging technologies. Conduct detailed structural, chemical, and electrochemical characterizations of synthesized hard carbon materials. Analyze material performance using advanced
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electrochemical characterizations of synthesized hard carbon materials. Analyze material performance using advanced techniques such as XRD, SEM, TEM, BET, Raman spectroscopy, and electrochemical testing
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of bioinformaticians, computer scientists, biotechnologists, biologists, and biochemists. The successful candidate will also enjoy an environment aimed to facilitate progress in the research career: networking, student
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essential step of the entire hydrogen chain. Owing to their light weight, high specific strength, good fatigue response, and dimensional stability, the use of fiber-reinforced plastic pressure vessels for
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applications. Improve material quality by reducing defects and enhancing large-area uniformity and continuity. Perform detailed structural, chemical, and electrical characterizations using XRD, SEM, TEM, Raman
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solvent extraction, membranes, and adsorption, for recycling and purification of selected elements from the cathode materials. System level performance optimization of metal recovery processes. Publish
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and technological challenges. In the Nature Index Rising Stars, KAUST was ranked #19 in the world of the fastest rising universities for high quality research output. KAUST was also ranked as the
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containment. The prohibitively high computational cost of such simulations necessitates the development of efficient and robust surrogate models for general GCS modeling tasks, especially when inverse modeling