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practical experience with various advanced polyolefins’ pretreatment methods (advanced chemical oxidation, UVc, ozone, plasma treatment, etc.), which will be used to improve degradability of the substrate. We
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at the intersection of advanced probabilistic machine learning and microbial bioscience. This position offers a unique opportunity for developing novel probabilistic ML methods with a view towards
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individual processes to entire manufacturing systems. The positions will all focus on factory and line level, where three research topics are defined: 1) Conceptual design principles and methods for resilient
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relating to thermal stress responses. Additionally, the postdoc will also be developing methods for integrating thermal tolerance measures with microclimate data from field sites and climate models to better
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national lab-based testbed on circular manufacturing, creating multiple demonstrators on how technologies aid in operationalizing circular manufacturing. This includes e.g. developing effective methods
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characterization in complex in-situ environments. The key responsibility of the position is to develop post-processing methods to extra essential features from the collected measurement data despite drone positional