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learning. You will be working in the research group of one of the PIs of the projects, but in collaboration with the others. The PIs are Talayeh Aledavood, Juhi Kulshrestha, and Mikko Kivelä. About the
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decade, providing opportunities to mine big data to learn more about the drivers of AMR in humans. Our work includes computational analysis of antibiotic resistance and microbiomes, statistical analysis
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opportunities means you will grow and learn, having the chance to participate actively in staff trainings and development projects based on your interests and needs. We value work-life balance and well-being in
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for immersive data simulation. Supportive, diverse, and inclusive research culture. Our wide range of professional development opportunities means you will grow and learn, participating actively in diverse
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data has increased massively in the last decade, providing opportunities to mine big data to learn more about the drivers of AMR in humans. Our work includes computational analysis of antibiotic
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. The department has a strong community on related topics: research groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will
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skills Competency in or willingness to learn process-based modelling Strong data management skills and proficiency with analytical tools e.g. Matlab, R, Python Previous experiences with eddy covariance
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. You will learn to communicate complicated topics in a clear and intriguing manner. The core values of the group are inclusion, equality, and collaboration. We value work-life balance and the wellbeing
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nora.lehotai@umu.se . Visit the NORPOD program page to learn more about the programme. We welcome your application!