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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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Doctoral School candidates must submit their application file to the doctoral program of their choice within the deadlines specified by the latter. Some programs publish open positions related
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element modeling, computational fluid dynamics). Knowledge of heat and mass transport processes in heat-sensitive materials and process optimization. Experience in supply chains and hygrothermal
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100%, starting January 2026 (negotiable) Proteins must fold correctly to function, and this process is tightly regulated by a network of chaperone proteins. At the heart of this network is Hsp90, a
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, Geophysics, Computer Science, or a related field. A solid grasp of general physics and a keen interest in the physics of wave propagation. Strong programming skills in Python, Matlab, or similar languages. You
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain. The Urban Energy Systems Laboratory...
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for biomedical applications. Your tasks Study the joint assembly of biopolymer in compartmentalized or bulk hydrogels. Characterize the resulting physical hydrogel properties as well as how these properties can be
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chemical and physical surface functionalization. The goal of the PhD project is to investigate how enzymes can be encapsulated in biocomposites to control both the assembly or crosslinking of biopolymers as
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materials and devices based on nanoscale surface effects, utilizing a combination of experimental and computational approaches. We are looking for a highly motivated PhD candidate fascinated by quantum
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Your position Our group conducts research at the intersection of artificial intelligence (AI) and pediatric healthcare, developing AI and machine learning (ML) methods to address real-world clinical challenges. Our core research topics include but not limited to the following...