Postdoc in Control-oriented model development and calibration towards digital twins for multi-energy systems
Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain
Design and implement digital twins for district energy systems. Focus on data-driven processes like data acquisition, storage, and analytics. Engage in model-based support, automated model derivation, and validation. Collaborate with external scientific and industry partners, as well as our interdisciplinary team. Mentor PhD students, publish in scientific journals, and participate in conferences. Your profile
Design and implement digital twins for district energy systems. Focus on data-driven processes like data acquisition, storage, and analytics. Engage in model-based support, automated model derivation, and validation. Collaborate with external scientific and industry partners, as well as our interdisciplinary team. Mentor PhD students, publish in scientific journals, and participate in conferences. Your profile
- A highly motivated and dedicated individual with a Ph.D. in applied mathematics, mechanical, environmental, or electrical engineering, or a related field.
- Good understanding of the ongoing energy transition in Switzerland and/or Europe.
- Strong skills in programming, modeling, and data analysis, especially in Python.
- Experience in mathematical optimization problems formulation and implementation.
- Proficiency in English; German skills are a plus.
- Knowledge of data management and analysis is desirable.
- Experience with semantic web technologies and open data formats, such as CityGML, is desirable.
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