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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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quantification. The specific project will be tailored to your expertise and interests; examples include: Efficient inference techniques for high-dimensional Bayesian inverse problems for image reconstruction and
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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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. Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ WIFORCE Research School Do you want to contribute to the future sustainable use of forests
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related to clinical imaging diagnostics. LUCI (Lund University breast Cancer Imaging) is an interdisciplinary group of scientists and medical professionals, mainly focused on innovative clinical imaging
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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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information can be found at www.slu.se/srh . Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ WIFORCE Research School Do you want to contribute
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neuronal connectivity in the brain. With live cell imaging, genetic perturbation, and transcriptomics (in collaboration: proteomics) we derive mechanistic insight into how ciliary signaling translates
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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
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doctoral student who has Competence and skills: -Strong foundation in computer vision (e.g., object detection, image segmentation) and NLP (e.g., text reasoning, language models). -Knowledge of generative AI