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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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, 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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, from basic research to more applied projects often focusing on sustainable chemistry but also advanced analytical methods of chemicals and materials. The department has a very well-developed research
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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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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
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capture methods lack sensitivity and often provide limited molecular information. In this project we will explore molecularly imprinted nanoparticle (nanoMIP) protein binders and mRNA and DNA probes
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LCA software (SimaPro, OpenLCA, Brightway). Skills in R or Python for data processing and analysis. Experience with soil or biodiversity monitoring methods. Experience using GIS (QGIS, ArcGIS