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CoSi project (Co-Evolution and Coordinated Simulation of the Swiss Energy System and Swiss Society), we are seeking a motivated and qualified PhD candidate to develop neighbourhood- and district-scale
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, potential toxicity and ubiquitous abundance in the environment. Understanding and evaluating their emission pathways is essential to plan and implement effective measures to reduce emission of PFASs. In
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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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. Our offer You will be enrolled in the doctoral program in Mechanical Engineering at ETH Zürich under the supervision of Prof. Dr. Dennis Kochmann and Dr. Jakob Schwiedrzik. This fully-funded and full
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programming, modelling and data analysis skills in Python and/or R. Experience with the formulation and implementation of mathematical optimization problems can give you a competitive edge. The candidate should
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science, and/or nanoscience. Prior experience with scanning probe microscopy, preferably with a focus on magnetic nanostructures or spin resonance studies, and programming in Python would be advantageous