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narratives to engage with more powerful actors towards transformative change. In addition, this project aims to include the element of ‘surprise’ by engaging with the non-linear dynamics (feedback loops and
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internationally outstanding research in the life sciences. Project description We seek two highly motivated postdoctoral researchers to develop new mathematical and computational methods for modeling developmental
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with
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methods and sample-preparation strategies; (iii) interpretable multivariate or ML models for classification and feature discovery; and (iv) high-impact publications and open, reusable analysis workflows
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, with joint academic–industrial supervision Data-driven life science is a field of research that utilizes data, computational methods, and artificial intelligence to investigate biological systems and
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in chemistry, physics and biology methods and concepts required to resolve the dynamic organisation of glycocalyces. The project will establish a new level of understanding of how glycocalyces perform
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missing physics rules to interpret experimental observations. The GLYCOCALYX Network will train 15 PhD Fellows in chemistry, physics and biology methods and concepts required to resolve the dynamic
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system and its repurposing into a tool for genome editing, a method developed at Umeå University that was awarded the 2020 Nobel Prize in Chemistry. The host lab is located within the cross-disciplinary
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Monetary Entrepreneurship. The position is open to candidates who prefer qualitative as well as mixed-methods research. Sten K. Johnson Centre for Entrepreneurship (SKJCE) is an active and internationally