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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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the health and performance of humans in several situations (e.g. firefighters, who are exposed to extreme heat, or older adults who are exposed to heat stress during heat waves) by modeling the environment
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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