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research opportunity focuses on advancing large-scale additive manufacturing using metal wire as feedstock and electric arc as the heat source. The project aims to develop an innovative and efficient method
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physics-based and data-driven methods to support the design and scale-up of these systems. This approach will reduce the need for costly experiments, improve scale-up predictions, and provide confidence
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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2 Mar 2026 Job Information Organisation/Company Ecole Centrale de Lyon Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application Deadline 31
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optimisation and learning-based control algorithms that can make decisions under uncertainty, using realistic network models and large-scale simulations. These methods will be evaluated on representative UK
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. Project description Flow in porous media is a ubiquitous phenomenon and relevant to many engineering processes, ranging from large scale carbon geosequestration and hydrogen subsurface storage to microscale
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to support large-scale studies Lead or assist with project coordination, data analysis, manuscript preparation, and grant development Engage in mentoring and training activities Qualifications Ph.D. in
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would be happy to discuss PhD projects related to these aims, as there is some flexibility in research directions. Characterise behaviourally-relevant visual and semantic dimensions by the use of large
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processes Reducing reliance on costly and hazardous precious metal catalysts. Delivered high-performing biocatalysts Engineered industry-ready enzymes suitable for large scale pharmaceutical manufacturing
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optical excitation, the energy is absorbed by the nanoagents, transformed into heat and then transferred to the surrounding medium. At the macroscopic scale, a continuous laser excitation of a collection of