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algorithms for Bayesian machine learning with applications in e.g., medical image analysis. The doctoral student position is offered within the machine learning project “The Challenges for Machine Learning in
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the 2025 Nobel Prize in Chemistry. Electron microscopy and electron diffraction offer powerful tools for advanced structural characterization. Aberration correction now enables imaging with true atomic
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dynamics to cellular metabolism. The student will receive broad training in cell culture, genome engineering, live-cell imaging, biochemical assays, proteomics, and computational data analysis, and will work
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and survival in host cells. Through a combination of microbiology, imaging, molecular biology, and translational modelling, the PhD student will generate data to support the design of biofilm-resistant
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electrolytes, primarily solid-state, for applications in Li-based batteries. Polymer synthesis, electrolyte fabrication, construction and testing of prototype battery cells are all parts of the project
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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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terrestrial laser scanning data (ALS, TLS), satellite and aerial images. Collecting field data as well as participating in burning experiments may also be part of the work. The research team includes expertise
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Electron Microscopy (TEM) and HAADF-STEM images. Microscopy data are often degraded by noise and scan distortions, and clean ground truth data are rarely available. This project aims to go beyond standard
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sensing data includes airborne and terrestrial laser scanning data (ALS, TLS), satellite and aerial images. Collecting field data as well as participating in burning experiments may also be part of the work
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methods and frameworks for IT/OT security, including analysis of vulnerabilities and threat images in converging system environments; requirements analysis in collaboration with total defense actors