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and flow field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision
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. Empa is a research institution of the ETH Domain. The Biointerfaces Laboratory is offering a PhD position focused on development of engineered antimicrobial hydrogels. This project aims to tackle
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, consumers, journal editors and guideline developers. Project 2: Integrating living evidence into adaptive platform trials to create efficiencies in research generation This project aims to explore
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primary supervision of Dr Thomas Ouldridge. The student will develop predictive models of nucleic acid strand displacement rates to allow the rational design of complex networks of ever-increasing
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involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim to build more trustworthy and robust AI models that can
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, which frequently produces designs that are suboptimal when subjected to real-world dynamic environments. Although a handful of advanced, high-fidelity solvers have been developed to tackle this issue
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systems for measurement processes, or innovative hardware and software for quantum computers and quantum sensors: we develop tomorrow’s technology in-house for a sustainable and secure society. Become part
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Max Planck Institute of Immunobiology and Epigenetics • | Freiburg im Breisgau, Baden W rttemberg | Germany | about 17 hours ago
epigenetics, biophysics, metabolism, biochemistry, cell biology, proteomics, bioinformatics and functional genomics. We train doctoral researchers to become self-reliant and to acquire and utilise the knowledge
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in all areas is not essential, as full training will be provided. Above all, candidates should demonstrate motivation, enthusiasm, and a willingness to develop new skills. Start Date: The successful
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and interests. Possible research directions include constructing multiscale simulation workflows and applying them to materials design, and/or developing and implementing novel machine learning