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also recognizes the unequal capacities and risks involved, highlighting the “cruel” ascriptions to optimism and the potentially devastating consequences of aspiration. ASPIRA's approach identifying
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) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software
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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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We are looking for a creative and hands-on Polymer Chemist with Formulation Expertise to join our growing team. In this role, you’ll play a key part in developing and optimizing innovative, bio
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that of CO2 and world-wide efforts are underway to develop and optimize equipment with environmentally friendly gas mixtures. The successful candidate will research (mostly experimental) on the arcing behavior
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100%, Zurich, fixed-term We are seeking a skilled Machine Learning Engineer to join our dynamic team. The ideal candidate will be involved in the development, optimization, and maintenance of our
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, optimized for high-performance computing (HPC) environments. Classifying ice crystal habits using Convolutional Neural Networks (CNNs). Providing intuitive graphical interfaces for user interaction and data
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) project, we are looking for a motivated and experienced PhD candidate to perform consumer flexibility aware planning of multi-energy districts. A particular focus lies on the modelling and optimization
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software tools, including applications in geoscience, optimization, and techno-economic modeling. Guide the team in modern software development practices (e.g., version control, documentation, testing
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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