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OF DOCTORAL STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22)Nº 117967 Where to apply Website https://www.upv.es/entidades/vinv/download/27300 Requirements Research
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project MetaExplore, coordinated by the University of Cambridge (UK) (https://metaexplore.eu/ ). MetaExplore has been set up to provide young researchers with hands-on research experience and formal
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decoupling the key thermoelectric characteristics using a “nanoparticle-in-alloy” design strategy within an inorganic thin-film system. The core objective of the research is to tailor the interface structure
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elaboration of biocatalysis for synthesis. A doctoral position is available for 3-years to work with Professor Florian Hollfelder at the Biochemistry Department of Cambridge University (https
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Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring
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initially limited to 3 years. Research project Advancements in structural biology and AI-guided protein structure design are providing new insights into the structures of receptors responsible for food taste
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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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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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support and mentoring for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz
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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