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characterization of glycoside hydrolases, and a postdoc working on computational modelling of the same enzymes. The PhD focuses on ligand-observed NMR analyses and other relevant methods to provide insight
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circular, economically viable future for packaging. Through SSbD assessment in collaboration with the consortium, experimental work and risk modeling, you will help uncover the hotspots in the production
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that these cells could be deployed to control intracellular S. aureus. The project will employ cutting edge technologies (transcriptomics, in vivo infection models, single cell metabolic analysis) to profile
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plant genetic mechanisms that coordinate mycorrhizal interactions with plant P and water status, root system development, and soil microbial communities. Using maize and rice as models, we will: Determine
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population projections and management of wild bird populations in times of climate change”, with the Seychelles warbler (Acrocephalus sechellensis) as a model system. The project is supervised by Prof. Hannah
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courses on quantum field theory and the Standard Model of particle physics.) Or you expect to obtain your Master’s degree around the starting date of the appointment. You are curious, communicative
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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metocean and biogeochemistry models accounting for climate change impacts across Europe (from the Nordic Seas to the Black Sea and Mediterranean Sea) and the Pan-Arctic region. The PhD project focuses on new
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models. This theoretical project will facilitate close collaboration with experimental groups and enable benchmarking of theoretical predictions. The PhD researcher will be part of the Correlated Quantum
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast