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unprecedented opportunities to revolutionize data analysis and simulation methodologies in the field. Job description The selected PhD candidate will join an innovative research team to explore cutting-edge
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methodology that develops physics-informed graph neural networks (GNNs) for composite space structure analysis. The methodology will aim to leverage the inherent structure of composite materials, embedding
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finalized after the selection procedure in collaboration with industrial partners. Job description You will work within the Computational Mechanics Group of ETH Zürich in collaboration with industrial
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support sustainable urban development and the well-being of their inhabitants. Project background This dissertation is part of the National Research Programme 81 (NRP 81 "Building Culture") of the Swiss
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/nanorobots, demonstrate targeted drug delivery with improved efficiency and reduced systemic exposure, and conduct an extensive performance analysis of biodegradability, magnetic navigation, and drug delivery
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rheological, thermal, mechanical and fire performance analysis of these CANs. Molecular structural characterization of the CANs with Solid-State NMR, X-ray analytics, Raman, AFM, etc., and relating the features
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related field. Programming, modelling, and data analysis skills in python and machine learning/optimization libraries/toolboxes support you in contributing to our ongoing software development efforts. Your
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Raman spectroscopy as a rapid, noninvasive, and label-free omics technology enabling metabolic profiling and biomarker detection in wound exudates. The project will be part of a larger Empa's initiative
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services. Develop your skills in spatial data analysis and statistics while working with diverse datasets to uncover important biophysical and socio-economic patterns. Be part of interdisciplinary
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the integration of passive and active supply concepts in the context of solar architecture and earth/wood construction. Project background This PhD position is part of the ThinkEarth project , a five-year