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developing AI methods for automated microstructure analysis and 3D microstructure generation. By combining self-supervised learning and diffusion-based generative models, the goal is to: Reconstruct high
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. The research school for stress response modelling in IceLab Starting in the spring of 2025, Umeå University’s interdisciplinary research hub, IceLab, will offer doctoral positions through the new Stress Response
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based integration of software-defined CPS (Cyber-Physical Systems) and IoT devices. -Replication and software updates during runtime for mission-critical devices and systems. -Model based engineering
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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environments with minimal environmental impact. We are recognized nationally and internationally for our excellence in numerical and computational modelling, experimental innovations, our collaborations with
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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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of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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format. This will allow combinations of neural networks with physics models. The project brings together PhD students and senior researchers from multiple disciplines to tackle challenges in sustainable
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. The student will work in a group addressing all these challenges, developing new AI-based methods to improve biological realism in simulations which will lead to more accurately inferred GRNs from real data