-
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
-
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
-
programming, modelling, and data analysis skills. Experience with formulating and solving mathematical optimization problems is an asset. Proficiency in English is required; good comprehension and oral skills
-
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
-
. 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
-
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