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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
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Your Job: We are looking for a PhD student in machine learning to work within a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop 3D+t
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experiments, behavioral research, econometric and causal inference approaches, optimization and analytical modeling, and data-driven techniques such as machine learning and large language models. Our work is
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Management Science, Information Systems Research, and MIS Quarterly. We seek applicants with a strong quantitative background, such as analytical modeling, econometrics, and/or machine learning, and a
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. Experience in molecular modelling, simulations, AI, and machine learning applied to proteins. A track record of research outputs, including publications and presentations at national or international level
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on applying computer vision, machine learning, and sensor fusion to automatically detect, classify, and localize defects, improving the scalability and reliability of building inspection. Research on 3D
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, collecting and analysing biomedical data, training machine learning models for bowel sound classification, and supporting prototype refinement and software integration for eventual commercialisation. Key