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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
-based digital twin, which can predict the assortment and sequence of two-dimensional all-DNA motifs required for the engineering desired tessellation patterns at the nanometer scale. We will use available
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/Diploma) in the field of Biochemistry, Biology, Pharmacy or Chemistry or related field Experience in experimental laboratory work Excellent knowledge of a broad range of biochemical, cell and molecular as
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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of the Open Competition Domain Science-M programme (Twenty-one innovative research projects awarded through Open Competition Domain Science-M programme | NWO - https://www.nwo.nl/en/news/twenty-one-innovative
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interfacing of the sensors. The PhD candidate will work at the Integrated Devices and Systems (IDS) group within the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University
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, PMID30224749 and PMID32743075 . Requirements M.Sc. degree in molecular-, cell-, structural biology, computer science, digital image analysis or related fields that included minimum six months long
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partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a
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“PhytoM - Leibniz Professorship for Phytonutrient Management” at the Technische Universität Berlin: PhD student (f,m,div) in the Field of Physiology and Food Chemistry Reference number: 21/2025/3 The salary
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highly motivated Doctoral Research Fellow in a full time (100 %) fixed term position available for three (3) years at the Faculty of Computer Science, Engineering and Economics, Department
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partnership with the German Federal Waterways Engineering and Research Institute (BAW); building a fully coupled model that simulates surface hydraulics and subsurface flow with relevant turbulence models and