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for innovation since the early days of machine learning. In particular, building on recent developments on VAE and diffusion models, we focus on the role of physics in generative models. In generative
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Vacancies PhD position on analysis of geometric machine learning methods Key takeaways We are looking for a motivated, theory-oriented PhD candidate to work on the project "A continuum view on
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quality photometry (from optical to near-infrared wavelength) for roughly 100,000 sources. This dataset represents an ideal input to train different machine learning algorithms to classify objects based
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experience in analysis of large microbial genomic datasets and design and validation of machine learning models. Metagenomics experience is an advantage. You have proficiency with programming languages e.g
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to staff position within a Research Infrastructure? No Offer Description Are you eager to apply cutting-edge machine learning techniques, develop innovative algorithms, and tackle real-life challenges
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Research Infrastructure? No Offer Description Leiden University is seeking an enthusiastic and well-qualified postdoctoral researcher in machine learning, in particular classification. The primary objective
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a: Postdoctoral Researcher in Machine Learning (1.5 years, 1.0 FTE), for the Project
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The project you will work on lies on the boundary between AI and theoretical physics. Physics has been a source of inspiration for innovation since the early days of machine learning. In particular
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nonlinear interactions at the origin of such extreme events. In this project, we will explore the use of cutting-edge scientific machine learning framework that blends deep learning with physics-based
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will explore the use of cutting-edge scientific machine learning framework that blends deep learning with physics-based techniques to achieve the goals of (i) identifying precursors and mechanisms