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components and nucleic acids interact and self-assemble. Apply data analysis and modeling to deepen understanding of nanoparticle architectures, and contribute to standardization-relevant method development
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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
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temperature and humidity data in cold chains by commercial sensors, and deploy them in end-to-end virtual supply chains. This project also aims to better understand the tradeoffs related to cooling technology
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. Historical data in the Empa's NEST demonstrator and its multi-energy back-bone will be utilized to design multi-energy districts. The candidate shall translate his/her research ideas to tackle these challenges
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of such tumors Establishment of a unique 3D micro-CT histology data base for recurrent thyroid carcinomas Data management, data treatment Extension and coupling with high-field MRI technology towards in-vivo
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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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/he will participate in writing scientific publications and presenting data at national and international scientific conferences. Previous experience in one or more of the following topics is required
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work closely with another PhD student and a post-doc to collectively investigate the failure mechanisms and the generation of high-quality sensor data. Your profile MSc in Materials Science or Mechanical