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of suitable catalysts and the optimization of operating conditions. This project aims to investigate the catalytic conversion of phenolic monomers via the catalytic hydrogen transfer process in both gas and
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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algorithms for entanglement distribution in quantum networks. The purpose of the role is to contribute to the project “Utility Optimization in Quantum Networks: Algorithm Design and Analysis”, working with Dr
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molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental protocols and equipment. · Design, execute and document experiments with sufficient detail to understand
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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the commissioning, optimization, and development of analyses for the ALPHA experiment. The candidate is also expected to take a leadership role in JHU-based testing toward the research and development of future
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refinement of innovative research methodologies and will independently design, optimize, and execute complex immunologic and molecular experiments across in vitro, ex vivo, and in vivo model systems. Technical
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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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an optoelectronic process for 980 nm high-power diamond laser diodes. In this context, the role of the LSPM is to provide polycrystalline diamond layers 2 to 4 inches in diameter with optimized mechanical
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thermoplastic feedstocks for FDM printing Programming of an existing hybrid FDM printing machine, including printing and milling devices Modelling and optimization of the debinding process Simulation-based design