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Field
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, or supervised/unsupervised learning depending on the available data) using spatial analysis and geographic machine learning tools (e.g., scikit-learn, PyTorch/TF + GeoPandas/Shapely) - Implementing a semantic
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theory, physics-based simulation, and machine learning. Job description The PhD project will develop machine-learning methods for atomistic materials modeling Possible research directions include machine
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of high-performance computer systems You preferably have experience with hydrology, and affinity or experience with agent-based modelling and large-scale data processing with societal relevance You are able
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methodological developments along the chosen direction (inference, active-matter theory, or machine learning). ◦ Algorithmic implementation and validation of the developed tools. 5. Validation on model systems
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. This research emphasizes improving prediction accuracy for renewable energy production (particularly solar and wind) through advanced machine learning techniques that capture spatial-temporal dependencies
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stays at foreign educational institutions Support to education activities in courses within the Software Engineering area Other career-promoting work, such as learning grant preparation fundamentals Be
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companies. Hybrid & Data-Driven Modeling: Apply machine learning and hybrid physics-AI approaches to model industrial systems, accounting for physical constraints, sensor noise, and heterogeneous datasets
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and experience with modern deep learning frameworks (e.g. PyTorch) Solid background in machine learning, ideally with experience in NLP, large language models, or sequence modeling Interest in clinical
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together to develop solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/phd-position-in-modeling-and-c… Requirements Research
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), Computer Science (Machine learning, Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Your project is part of the DUAL-IMPACT project, which focuses on the development