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Description The main tasks to be carried out by the selected candidate will be the following: ● Develop new methods for the uncertainty quantification of non-linear statistical models using the 'online
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 1 month ago
the information they contain. This project, part of the Helmholtz School for Marine Data Science (MarDATA), will develop new data science methods to improve the interpretation of biodiversity patterns from long
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on ultrafast chirality and attosecond electron dynamics, aiming to develop new methods for probing and controlling chiral light–matter interactions with applications in photonics, biosensing, and materials
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, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our people make the difference. With
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throughout the period of performing the project tasks, subject to the exceptions provided for in the NCN regulations; education or research experience in computer science, artificial intelligence, machine
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to characterise how individual MNs influence mitochondrial function and metabolic pathways in peripheral blood mononuclear cells. This position is ideal for someone with a strong interest in experimental cell
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on the intersection of learning theory, PDEs, and systems & control, likely using RKHSs (or similar function spaces), Koopman operators, and neural networks to study interesting classes of controlled PDEs, develop
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. Griffin Graduate School of Arts and Sciences, founded in 1872), Harvard Athletics and the Division of Continuing Education. The 40 academic departments and 30+ centers of the FAS support a community
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at the intersection of AI, deep learning, computational neuroscience, and vision science. You'll develop biologically realistic neural networks to understand how individual differences in the brain shape perception
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, resulting in inconsistencies across soil properties and underperformance in data-scarce regions. This PhD project will develop next-generation machine learning methods for geospatial prediction by integrating