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processing approach based on flow patterning to make meter scale LCEs of complex shapes and actuation modes. ALCEMIST builds on a tight synergistic collaboration between the Experimental Soft Matter Physics
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weather prediction using Machine Learning approach (hybrid forecast). The app is also expected to be equipped with seasonal forecast for agricultural planning. You will co-design the short-, medium-, and
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machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens
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PhD studentship associated with a Collaborative Partnership between RNCM and Olympias Music Foundation (www.olympiasmusicfoundation.com ) The RNCM and Olympias Music Foundation are delighted
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, where opportunities for collaboration and learning abound. About the role The role involves undertaking high quality research as part of an exciting new internationally funded research project
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. This comprises learning to set up and operate our new optical cryostat platform, which involves advanced confocal microscopy, laser pulse shaping, and time-bin interferometry. (b) You will benefit from our
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to make decisions, solve problems, and learn. Moving from rule-based systems to agents with strategic flexibility. The range and complexity of tactics, techniques, and procedures that are supported, as
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benefit sharing. The candidate will work on several case studies, including a case study in Northern Kenya in collaboration with the Wyss Academy for Nature (University of Bern). Your job Despite the
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-impact research and dissemination, help secure extramural research funding, support the management of research facilities, and engage in collaborative efforts across departments and institutions. This is a
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meaningful questions, and possess the determination to pursue innovative solutions in a rapidly evolving technological landscape. DTU Wind and Energy Systems, in collaboration with Vestas - the world’s leading