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their ability to: independently pursue his or her work collaborate with others, have a professional approach and analyze and work with complex issues. Experience in machine learning, algorithmic theory, or code
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information about us, please visit: www.dbb.su.se . Main responsibilities SciLifeLabs Cell and Molecular Imaging (CMI) platform offers access to advanced imaging technologies, from cryo-EM and tomography
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using Cell Painting and high-content imaging. Deep learning and multivariate methods, both supervised and unsupervised. Development of software and pipelines for analysis of large-scale image data
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, BCI), physiological data, and medical image/microscopy analysis. Excellence in foundational and applied research, demonstrated by publications in leading AI/ML and medical imaging venues (e.g., MICCAI
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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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Proteomics unit you will be responsible for data management and infrastructure, implementation and development of analysis pipelines. You will work on different datasets and help our users with image and
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of the identified structures via stereolithographic, 3D printing and textile techniques like tufting, machine-based embroidery techniques or non-interlaced 3D pre-forming. Development of advanced imaging and
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through advanced mass spectrometry imaging (MSI) technologies. The employment will be placed at the Department of Pharmaceutical Biosciences , at Uppsala University. Key Responsibilities Perform
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tissue using spatial transcriptomics, electrophysiology, imaging-based assays, and integrative data analysis. The goal is to map disease-related cellular states and spatial patterns of dysfunction in
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nanoscale X-ray diffraction (XRD) methods to image domain dynamics in ferroelectric materials. These are characterized by the existence of domains in which there is an aligned polarization, similar