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project. The project will also employ a PhD student at Lund University, focusing on developing hybrid architectures for deep learning-based image processing and methods for multimodal medical data. We will
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. You also have substantial experience in a laboratory research environment. You should have prior experience with experimental molecular biology techniques, tissue processing and imaging. You also have
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-dimensional Bayesian inverse problems for image reconstruction and chemical reaction neural networks with sparsity-promoting (and edge-preserving) priors, including diffusion-based approaches. Neural solvers
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conventional harvesting. The research will involve practical DNA sampling, high-throughput genotyping, and data fusion using machine-generated harvest data, annotated images, and environmental information
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requirement. A very good command of the English language, both written and spoken, is a key requirement. Experience in Federated Learning, Computer Vision, Image Analysis, Mathematics, and Mathematical
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complex systems. Development and application of theoretical tools that combine experimental data and atomistic computer simulations to provide a comprehensive picture that is difficult to achieve through
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its dependency on the pre-fire forest structure and management practices in Fennoscandian boreal forests. Work includes e.g. developing methods to assess burn severity and fuel structure, processing
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fuel structure, processing of different remote sensing and mapped data, statistical modelling, mapping of fire risk and analyzing the effect of forest management for fire behavior. Considered remote
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, diagnosis, drug response and health monitoring. Research in precision medicine is expected to use existing strong assets in Sweden and abroad, such as molecular data (e.g. omics), imaging techniques
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understanding and innovative fabrication processes to solve urgent problems in organic electronic devices, and enable new components with sustainable functionalities. Collaboration with industry partners will