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energy system models that incorporate a stronger Social Sciences and Humanities (SSH) perspective. By embedding societal dynamics, such models aim to capture a wider range of future uncertainties and
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of the PhD project is to investigate how biopolymers and biocolloids can be tuned into stimuli-responsive reactive and non-reactive inks for advanced assembly (3D printing) of bio-composites. We envision
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well as the disassembly or reassembly of the materials into new composite structures. We envision that the generated knowledge will advance the field of bio-based and sustainable material technologies and contribute to new
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-ceramic composites in close collaboration with a PhD student at the Biomaterials Engineering Group at ETHZ and the identification of process-structure-property relationships enabling the efficient design
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layers, thorough FLA processing, and extensive materials characteri-zation using XRD, electron microscopies, TOF-SIMS, electrochemical methods, etc. Modeling and simulations should help us to explain
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their subsequent simultaneous analysis. This project aims at overcoming these challenges to reliably measure atmospheric levels of PFASs and model their respective emission strengths in Switzerland
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nanoparticle systems. Investigate model particles such as liposomes, mesoporous silica and silver nanoparticles. Investigate RNA-LNP formulations for next-generation gene therapeutics, examining how lipid
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the esophagus with relevance to eosinophilic esophagitis. The research project will involve patient-derived samples, including organoids and air-liquid interface cultures, and experimental esophagitis models
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. Empa is a research institution of the ETH Domain. Empa's Laboratory of Biomimetic Membranes and Textiles is a pioneer in physics-based modeling at multiple scales. We bridge the virtual to the real world
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understanding of district heating and cooling, renewable energy integration, multi-energy systems, and energy conversion and storage technologies. You have strong skills in programming, modelling, and data