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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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years according to central collective agreement. Full time position. Starting date as agreed. Placement: Uppsala For further information about the position, please contact: Ruisheng Xiong (e-mail
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, serving the SciLifeLab infrastructure and the Data Driven Life Science (DDLS) research program. The Data Centre has a national assignment and operates a range of life science data and e-infrastructure
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is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university
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life sciences (DDLS). We have a national assignment and operate a range of services for life science data and e-infrastructure. We also work with issues about FAIR data and open science, and in close
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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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to integrate research in the relevant subject area, subject didactic, and higher education into teaching is also required. documented ability to teach in Swedish or English. In addition to academic
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++ or similar) and an interest in quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not