Job description
The goal of this position is to lead the energy system optimization sub-group of the Reliability and Risk Engineering Lab.
To this aim, the successful candidate will :
- Advance mathematical optimization methods to further our understanding of future energy systems
- Conduct interdisciplinary analyses related to future energy systems, e.g., energy policy, behavioral economics, climate modeling, risk management
- Contribute to national and international projects in the field of energy systems transition
- Supervise doctoral students in the field of energy system optimization
- Contribute to shaping the research mission in the energy system modeling group at the Reliability and Risk Engineering Lab
To address these points, you will have access to state-of-the-art computational capabilities, and you will be in contact with experts within ETH Zurich and worldwide.
Your profile
We are looking for highly motivated and self-organized individual with a PhD in engineering or in a quantitative discipline (such as applied physics, mathematics, or economics) from an internationally recognized university and an excellent academic track record.
Successful candidates have a background in energy system optimization, quantitative modeling, and programming (e.g., Matlab, Python, Julia, GAMS) with a focus on multi-energy systems, sector-coupled energy systems, energy networks, and / or transition pathway models, and a demonstrated knowledge of mixed-integer linear programming solvers (e.
g., CPLEX, Gurobi, MOSEK) and of modeling environments (e.g., Yalmip, Pyomo, CVX, CVXPY). Knowledge of uncertainty quantification is a plus.
We require excellent communication skills in English, both verbal and written. Knowledge of German is welcome.
You should combine strong individual research with teamwork and leadership capabilities to guide the energy system optimization sub-group of the Reliability and Risk Engineering Lab.
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