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Project description The postdoctoral fellow will explore synaptic processes and white matter pathways between remote brain areas in vivo in animal models that underlie plasticity in the prefrontal
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on processing and analyzing large sets of medical brain imaging data. We have amassed large quantities of structural MRI (used to measure brain structure), diffusion MRI (used to measure brain connectivity) and
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to increase chances of forming a strong and complementary team. Close dialogues will be held between the recruiting units during the process. Job description The Spatial Proteomics Unit is seeking a motivated
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development for imaging liquids and solid–liquid systems at the nanoscale. Collaborate with researchers at Chalmers and beyond, and share knowledge with the wider microscopy community. Publish and present your
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models using advanced operator learning and physics-informed AI techniques, leveraging high-resolution X-ray imaging data and high-performance computing (HPC) resources. The position offers a unique
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fluid dynamics and vascular modeling in microenvironments Skills in data analysis and image processing (e.g., Python, R, ImageJ) Ability to mentor junior researchers and contribute to team leadership What
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Cancer is a leading cause of death globally, and analyzing digital pathology images for cancer diagnosis and treatment is a complex problem due to the high data volume, variability, and computational
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, deep learning, and human computer interaction. Furthermore, this university is Sweden’s leading university in industrial collaboration. The Machine Learning (ML) subject at the department
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microscopy workflows to study battery materials and interfaces. Work with new approaches for preparing and transferring sensitive samples. Contribute to method development for imaging liquids and solid–liquid
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processes such as metabolic flux readouts and analyses of signaling pathways. In this way, the project integrates discovery-based proteomics with mechanistic experiments to directly link protein localization