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be a game changer. Deep learning models can learn the mapping between material states and ultrasonic responses from simulation data, delivering quantitative predictions once trained, and remarkably
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Knowledge of machine learning, Large Language Models (LLMs), Vision Language Models (VLMs), or generative AI Experience with Retrieval-Augmented Generation (RAG), AI agents, model-driven engineering, DevOps
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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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and economic use of renewable electricity without an unnecessary discarding of generated power. This four year’s PhD position is aimed at developing multiphase models to predict the dynamics and
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inverse problems, as well as the development of numerical methods that can eventually be applied to large-scale wave-imaging problems. The PhD project will have a strong mathematical component. You will
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31.07.2026, Academic staff We are seeking a researcher in Scientific Machine Learning (SciML) to join the project "Data science at scale" at the Technical University of Munich, Germany. Ideal
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 3 months ago
for a PhD student to join a project at the interface of biomolecular dynamics and modern data science (ERBIOM project). Our group has a long-standing track record in molecular modeling, molecular dynamics
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
applications will be tackled. The first concerns electrical machines like power plant alternators for which EDF has developped numerical simulators and has large sets of sensor data (measuring leaking flux
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team of data