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informatics. This, to serve the biological goal of mapping out the breast cancer tumor microenvironment, understanding the regulatory signaling network, and identifying early stage progression markers and
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networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
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Python or R are required. Basic understanding of statistical analysis in large dataset is expected. Fluency in written and spoken English. Merits: Experience in applying machine learning and/or network
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that the applicant has Collaboration skills and the ability to create and maintain international networks. Ability to collaborate with external stakeholders, such as healthcare, authorities, and companies
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the past ten years thanks to artificial intelligence, mainly in the form of deep convolutional neural networks. In parallel, functional analysis of tissue samples via novel microscopy techniques and spatial
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for cancer research and diagnosis as well as graph neural networks for microscopy. Main responsibilities The position involves taking an active part in CMCB lab’s daily research. The succesful postdoc will be
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Uppsala and in Sweden at large. For information about the SciLifeLab fellow program, see https://www.scilifelab.se/research/#fellows. SciLifeLab Fellows are also part of a broad national network of future
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to join a network of next-generation data-driven life scientists. The program aims to build strong, globally competitive computational and data science capabilities within Swedish life science. Eligibility
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provides excellent access to research infrastructure, including databases, computational facilities and instrumentation, as well as to clinical materials and networks and training activities. The four
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technologies like normalizing flows, graph neural networks, and transformers to represent distributions over trees, to improve MSC estimation. These technologies have shown significant improvements in