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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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methods/simulations, state-of-the-art computational techniques (e.g. data-driven methods and/or FEM) and/or theoretical material modeling will be given preference We offer: chance to collaborate with
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in Southeast Asia with the capacity
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consisting of PAT and mechanistic / data driven modelling allowing process control. Steps to be taken will be: Developing a process applicable PAT method (single / multisensoric) for AAV / LNP / VLP detection
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the technical and social challenges of Advanced Air Mobility (AAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in
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model complexes. This research is part of a large, funded collaborative project supported by the Swiss National Science Foundation, involving partner researchers based in Germany, Switzerland, and France
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry
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, master’s degree) in transportation, computer science or related fields experience with transport models and/or simulation tools interest in interdisciplinary research on the analysis and modeling
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offering PhD positions for students with a background in data science, computer science, computational science, or a domain science with a strong focus on computational science, and an interest in training
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). The goal of this collaborative project is to model the entire lifecycle of offshore wind turbines—construction, operation, and decommissioning—within a comprehensive digital twin framework. Your tasks As a