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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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transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition
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, have a professional approach and analyze and work with complex issues. The following qualities and experiences are considered meriting beyond the general selection criteria: Experience in machine
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Python and/or R for bioinformatics and ability to write clean, reproducible, and well-documented code for complex multi-step pipelines. have documented experience from cancer research. Additional
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collaborate with others, have a professional approach and analyze and work with complex issues. Previous experience working with method development in spatial omics is considered a merit. After the
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services allowing integration of large language models, foundation models focused on life science data, and narrow models in complex research workflows (for example, through AI agent architectures
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principles and approaches for managing and sharing different types of research data, as well as being engaged in competence-raising networking within research data management in Sweden. To perform the work
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transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition
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of the work is also to educate researchers in principles and approaches for managing and sharing different types of sensitive research data, as well as being engaged in competence-raising networking
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of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as flow matching. Therefore, the doctoral