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engineering, computer science, data science, or a closely related discipline Have an excellent academic record Have strong analytical skills Be passionate about sustainability, energy, and public policy Be
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experience in statistical analysis and implementing machine and deep learning models using Keras/TensorFlow and/or PyTorch. You have experience in collaborative coding, version control, and utilizing computer
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. Integrate various datasets, such as tree species annotations, climate, and topography, into deep learning algorithms. Test deep learning models (Transformers and CNNs) for optimal accuracy using large
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(IVT) at ETH Zurich intends to develop scalable optimization systems for operational support in large-scale road networks. Modeling and simulation are powerful tools for the development and validation
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the impact of alloying on the magnetic properties of Sm-Co magnets, using Fe-Cr as a test bed material. This project combines advanced experimental techniques with computational modeling, including: Advanced
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headed by Prof. Iber, which leverages imaging data to develop data-driven, mechanistic models of biological processes. The team employs cutting-edge computational tools and imaging techniques
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Developmental Medicine will probe and integrate multi-omic data sets (i.e. genetic, epigenetic, transcriptional and metabolomic data) to create computational models defining the molecular signatures underpinning
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100%, Zurich, fixed-term The Computational Mechanics of Building Materials in the Institute for Building Materials at ETH Zurich has an opening for a PhD student in modeling fracture in soft
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of computational and statistical genomics, and bioinformatics. Cattle are an interesting «model organism» to study inherited genetic variation and the molecular-genetic underpinnings of complex traits and dieseases
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Your Tasks: Develop AI-based optimization methods to enhance industrial manufacturing processes Design and implement cutting-edge machine learning models for process parameter selection Reduce