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Field
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trade-off and scenario analyses? Then this may be the perfect postdoc position for you! As Postdoctoral Researcher in Scaling Soil Moisture Retention (SMR) Practices you will play a key role in the
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. The workplace is at BUILD at Sydhavn in Copenhagen. Your work tasks To prevent fungal growth, it is necessary to know how biobased building materials react to water and under which moisture and temperature
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polymer brush architectures with dynamically tunable wetting, solute transport, and trapping properties. The work connects fundamental polymer and soft-matter physics with concepts from intelligent
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with dynamically tunable wetting, solute transport, and trapping properties. The work connects fundamental polymer and soft-matter physics with concepts from intelligent materials and bio-inspired
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transcriptomic analysis, multi-omic integration, and interpretation of developmental datasets. Depending on your profile, the balance between wet-lab and computational work can be adjusted within the scope
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, through the addition of a small amount of an additional element (i.e. considered as dopant), a partial transition to the liquid state to wet the AHE grains, and (ii) in-situ deoxidation to trap native
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Postdoc – Performance requirements for biobased construction materials used in the building envelope
of materials to provide the basis for formulating new standards using biobased materials in the building envelope. Your main responsibilities will include: Providing scenarios for moisture-related challenges and
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and spoken English. Ability to work both independently and collaboratively in an interdisciplinary research environment. Wet lab experience (depending on the work to be developed). Environment
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frameworks with wet-lab validation in human iPSC-derived neural models, organoids, or in vivo systems. Exploring translational applications, such as AI-guided mRNA therapies or precision modeling
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) perform in-silico interventions (e.g., gene knock-outs) that create testable hypotheses that will guide future wet-lab experiments. Your mission Lead the development of mechanistic machine learning models