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stress influenced by the frequent winds. The objective aims to generate year-round climate-responsive design strategies, while producing structured spatio-temporal datasets that will serve as input
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Infrastructure? No Offer Description Join the ERC-funded GeoTrAnsQData project and explore hybrid AI approaches to better understand, structure and formalise geo-analytical questions. This helps shape the future
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candidate will be anchored in the Belowground Crop Ecology group in the Crop Sciences section within the Department of Plant and Environmental Sciences, Faculty of SCIENCE, University of Copenhagen (https
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within the Graduate School Language & Literature at LMU Munich offers excellent conditions for doctoral research. Our program combines a research-oriented and systematically structured interdisciplinary
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
Your Job: The field of structural DNA nanotechnology holds a great promise for the realization of all-DNA building blocks with arbitrary complexity and shape at the sub-nanometer scale
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the structure of para-aminobenzyloxycarbonyl (PABA) linker units. By altering substituents around the PABA core, we will investigate how electronic and steric effects influence payload pKa and, ultimately
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they will develop synthetic skills in organic and coordination chemistry, analytical skills in the collection, analysis and interpretation of key data using a range of techniques to characterise structures
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March for the following winter semester Submit application to https://hbrs.cloud.opencampus.net/ (Platform opens between 1 December and 1 March.) Accommodation Accommodation in a students' hall of
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international, interdisciplinary, and diverse team within an open-minded environment. Enrol as a PhD student in a structured doctoral program that offers a comprehensive and exceptional qualification curriculum
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FOR DRAWING UP OF PREDOCTORAL CONTRACTS FOR THE TRAINING OF DOCTORAL STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 119865 Development of machine-learning and graph-based models