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Postdoc in Generative Machine Learning for Biomedical Data | Human Technopole, Milan Build the science that shapes the future of human health. Application closing date: 21.02.2026 Join a place where
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ICT Services & Applications. Your role This position sits at the interface of machine learning, uncertainty quantification and computational biomechanics. You will work within the Legato group and in
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microscopy data analysis, chemometrics, and machine learning. This position is ideal for a researcher who enjoys working at the interface of imaging, data science, and environmental monitoring. The project
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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Description VIB.AI, the VIB Center for AI & Computational Biology, is a young research center dedicated to combining machine learning with in-depth knowledge of biological processes. Our mission is
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or machine learning, proficiency in deep learning techniques (CNN, VIT, diffusion, GAN) Good understanding of the mathematical foundations of machine learning Mastering python and related AI software
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to work on the discovery of new superconducting materials with high critical temperatures, using novel methods and concepts such as machine learning and quantum geometry. The project is related to large
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human health. Within this mission, the Iorio Group works at the intersection of computational biology, functional genomics, and precision oncology, integrating machine learning, large-scale CRISPR
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, biology, computer science or related disciplines Strong computational skills, including machine learning, e.g. demonstrable project in a relevant field A strong first-author publication record in a relevant