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Field
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training dataset of well-studied volcanoes with known large eruptions, the project will employ statistical and machine learning (ML) methods to identify the strongest predictors of eruption magnitude
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
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: Machine Learning Molecular Dynamics. The project involves the development and application of machine learning methods that enable a major boost of the time and length scales accessible to ab-initio/first
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applicants who have a background or strong interest in Computer Science, interactive media, software engineering, 3D modelling/animation, VR/AR, human–computer interaction or related digital-tech fields
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new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will benefit from the extensive and broad
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equations to simulate pollutant transport, mixing and biochemical processes. To enable rapid prediction, a machine-learning surrogate model based on Gaussian process regression will be developed and trained
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certification, dramatically accelerating innovation cycles. What you will gain: Expertise in Finite Element Analysis, Scientific Machine Learning, Uncertainty Quantification, and Professional Programming
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, machine learning, or (astro-)physics (in particular cosmology, galaxy formation, or general relativity) will be an advantage. What we offer: Inspiring working atmosphere: You will have the opportunity
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these syndromes occur where and when they do? The student will develop statistical and machine learning models to (i) explain the occurrence of extreme fires and (ii) predict their likelihood under present and
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shaving/shifting, voltage and frequency support, and virtual inertial response. Due to the volatile and intermittent nature of RESs, in this project, machine learning (ML) methods are used to accurately