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Field
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with competitive salary according to ETH standards Interdisciplinary and international research environment You can expect numerous benefits , such as public transport season tickets and car sharing, a
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-state model will be approximated using machine-learning surrogates and will be used for a real-time optimization, such that the plant operates optimally despite disturbances. The candidate will be part of
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descriptors to support machine learning model development to accelerate materials discovery: Perform high-throughput DFT and molecular dynamics simulations to investigate the thermodynamic, structural, and
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such as surgery, patient or staff scheduling using, e.g., multi-objective optimization or machine learning approaches and analyzing efficiency-fairness trade offs. The research will be conducted under
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25th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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systems, and space applications. We combine theory, physics-based simulations, machine learning, and autonomous workflows to understand and design materials that can perform under conditions where
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contribute 1) to the analysis methods and metrics for understanding the complex interactions between forage resource and dynamics; 2) to develop Machine Learning methods for analysing sensor data on animal
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better capture the dynamics of urban infrastructures
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of dissertation topics: Developing Remote Sensing–Based Indicators of Landscape State and Change Using Data-Efficient Machine Learning Across Scales Profile of the graduate The graduates have deep theoretical