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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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· Develop and apply transformer-based foundation models and machine learning methods for large-scale epigenetic datasets · Integrate longitudinal data and biological prior knowledge into AI models · Actively
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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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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dynamics. Particular emphasis is placed on opinion dynamics as well as distributed problems in coordination, optimization, and learning. The research encompasses both theoretical and computational aspects
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related field and have previous academic experience in machine learning. The candidate should have a strong background in metrology and medical image processing. Active participation and collaboration
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, and registry-linked outcome data. In this project, you will develop and apply AI-based methods (e.g. machine learning methods and many other methods) to harmonize historical and current pathogen
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of algorithms, data structures, high-performance computing, machine learning and microbiology. The position at the Department of Molecular Biology at Umeå University is temporary for four years to start
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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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 as a workplace Application deadline 2026-02-27