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This research position focuses on simulation of building and communal energy systems, thermal energy storage and their integration in district heating networks in an interdisciplinary collaboration of researchers and Swiss industry partners.
Departement:
Arbeitsbeginn:
Ihre Aufgaben
We offer a time-limited position until end of 2027, with the possibility for extension, as a scientific collaborator with research focus on simulation of building and communal energy systems. The position is part of the Innosuisse Flagship project "SwissSTES - Swiss Seasonal Thermal EnergyStorage Action Plan and Implementation" and other related research projects. Your work includes the following responsibilities:
Supporting ongoing research in building and urban energy systems simulation, including seasonal thermal energy storage (STES) and district heating networks
Performing building energy systems and thermal network simulations
Thermal energy system optimization, exploring component sizing and control strategies
Performing spatial, multi-criteria analysis (GIS) for identification of renewable energy and thermal storage potentials
Data handling and automatization of workflows, categorization/clustering
Taking over/supporting project lead
Writing technical/project reports
Authoring/co-authoring articles in scientific journals
Supporting the acquisition of research projects / proposal writing
Ihr Profil
We are looking for a widely interested and open-minded person who likes to work in an interdisciplinary team, at the interface between building systems, architecture and construction and supports our team with new ideas and solid research work. Sucessful candidates should bring:
Master degree in engineering, physics or related fields with knowhow in building/urban energy systems
A PhD in a related field is recommended
Good mathematical modelling skills
Expertise in conducting energy demand simulation at various scales, from individual buildings to the district level, using both top-down and bottom-up approaches
Experience in processing climate scenario and weather data from different source
Experience in scripting/programming in PYTHON, ...
Experiences with GIS analysis and data-driven methods is desired (understanding of clustering and spatial interpolation algorithms)
Experiences with district heating systems is a plus
Fluency in English oral and written, German level B1 and above desired
Dafür stehen wir
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