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developing complete models. Example applications include models for predicting material structure and properties, neural networks replacing quantum chemistry with knowledge-based approaches, improved materials
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developing complete models. Example applications include microscopy image data, cryo-electron microscopy, structural prediction and dynamic simulation of biological macromolecules, genomics data, and
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acclimate to a changing world and how we can breed better plants. About the position In this project you will develop and apply statistical and genetic models: Research-focused work on creating and using
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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This multidisciplinary position is part of a WASP NEST (Novelty, Excellence, Synergy, Teams) project focused on advancing generative models and perceptual understanding in computer vision. The
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to emerging digital technologies Interplay between technology development and business model evolution - how advancements in technologies reshape value creation and value capture, necessitating continous
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. You enjoy combining experimental laboratory work with theoretical analysis and modelling. While your main focus will be the research project and your own development as a researcher, the position also
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utilized to mitigate flooding risks through hydrological modelling and stakeholder engagement.Focusing on the Gothenburg region, the project will: Identify roads suitable for climate adaptation in three
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to the development of ongoing research. This will include the integration, modelling, and advanced statistical analyses of large genetic, ecological, and environmental data sets. The successful candidate is also
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cancer. The goal will be to find genetic prediction models to be able to predict which childhood cancer patients have a high or low risk of toxicity in childhood cancer. Preliminary the doctoral project