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willingness to learn A solid foundation in experimental research, data analysis, and scientific methods Interest in machine learning and data-driven approaches to materials discovery Strong interest in hands
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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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a multidisciplinary environment, driven by scientific curiosity and open to learning new topics. The Ph.D. candidate needs to be proficient in spoken and written English and have a Master's degree. S
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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