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microbial metabolites and its effect on chronic kidney disease and cardiovascular complications, using an in vivo model of chronic kidney disease. Responsibilities and qualifications As a PhD student, you
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
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to mechanical forces. We work with leading international groups on modeling and also conduct simulations at DTU. Our overarching goal is to understand and predict the mechanical behavior of metals during plastic
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research focus will include some of the following topics: Advanced sensor fusion and multimodal AI models for robotic intercropping. Self-supervised learning will generate multimodal agricultural pre-trained
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conversion. The project partner at TUM will focus on the materials production, stability characterization and the catalytic activity tests aspect of the project. The work at DTU will focus on the materials
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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-cutting and bending to break the glass panels. The project will involve the establishment of a numerical model and the acquisition and analysis of data from physical measurements in the production