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, evaluation, and interpretation of AI models on single-cell biological datasets, while keeping downstream translation and valorization potential in clear focus. Key responsibilities Apply and evaluate advanced
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the Telemark Canal , focusing on digital twin-based preparedness modelling for cultural heritage infrastructure. The primary objective of the position is to complete a doctoral education leading to a PhD degree
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Application deadline: 31/03/2026 Research theme: Biocatalysis and Protein Engineering Centre for Sustainable Synthesis – BioProcess How to apply: https://www.mib.manchester.ac.uk/research/centres
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, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical composition and atomistic modeling
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and tectonic significance of these inferred basement structures remain insufficiently constrained. The overall objective of this PhD project is to test and refine existing structural models by
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integrating statistical-mechanical theory, quantitative modeling, and experimental single-molecule methods. We aim to develop mechanistic models of receptor activation that combine physical theory with data
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activities: 1. Identification and specification of requirements for the development of an educational game within the scope of sustainability and the circular economy of the STV. 2. Design and modelling
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Description We invite applications for a fully funded PhD position within the DFG Priority Programme SPP2389. https://tu-dresden.de/mn/biologie/allgemeine_mikrobiologie/spp2389?set_language=en
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for biological data (e.g., protein language models, transformers, generative models) and interest in building interpretable tools for experimental colleagues. Qualifications PhD or MD‑PhD in a relevant field (e.g
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for students with BSc degree with reference number BI|2026/880 under the scope of the Projet SALVE: Securing Artificial Language Models Against Vulnerability Encoding (2024.14936.PEX), funded by Fundação para a