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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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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
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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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), Nouryon (chemically modified fibers and industrial context), and KTH (cross-validation and imaging). Work primarily at Chalmers and the Swedish NMR Centre in Gothenburg, with regular interaction across
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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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, 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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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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processes to human health and ecosystems. As part of SciLifeLab, a unique nation-wide infrastructure and research community that combines advanced life science technologies with data and AI expertise
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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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to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven