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advanced AI methods to extract meaningful knowledge from large-scale, heterogeneous, and high-dimensional biomedical and population data, often referred to as Big Data in the health and life sciences
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Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your
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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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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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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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symptoms emerge. The group combines large population-based and twin cohorts with longitudinal blood-based biomarkers, multi-omics data, and advanced epidemiological methods. The group is part of the research
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by developing data-driven approaches to identify and prioritize isoform-specific therapeutic targets, enabling a new level of precision in RNA-based treatments. The project will combine large-scale
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. Uppsala has two universities and with more than 50,000 students, a vibrant reserach-oriented student atmosphere. More information about the department/division: https://www.slu.se/institutioner/vaxtbiologi
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of ion conductivity in complex battery materials on a large scale. Model‑generated data will be used to identify key relationships between material structure and ionic conductivity through advanced data