PhD Student

On risk-averse energy markets with flexibility of storage

Your tasks

  • Achievement of a PhD degree at ETH Zurich on cutting-edge mathematical analysis of energy markets where risk-averse market players use storage technologies and financial hedging instruments
  • Development of the methodological basis and model-based application related to electricity markets with an increasingly higher level of storage possibilities
  • Assessment of optimal financial hedging mechanisms for different types of risk-averse players on energy markets, including barriers for their adoption and optimal usage
  • Estimate players' benefits, social costs and market price impacts under different assumptions on risk measurement and perception, and different degrees of market completeness
  • Analysis using financial hedging/replication theory, adopted to energy markets, under different assumptions of financial risk measurement; corresponding numerical analysis with a market equilibrium model
  • Dissemination and publication of research in academic journals and at conferences. Support teaching activities and specific other scientific tasks of the group

Your profile

  • Very good mathematical skills
  • You have (or are about to get) a master degree in operations research, mathematics/finance (especailly financial risk management and hedging/option theory) or economics/energy-economics (with master courses taken in operations research, math or finance)
  • Mathematical optimization software skills are beneficial (i.e. GAMS)
  • You have good written and verbal communication skills, and enjoy working in an international team. Good English language skills are essential
  • You can provide in your submission a recommendation from a person in the field of either operations research, mathematics, finance or quantitative economics.

We offer

Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from a systematic training on the job, in addition to personal development possibilities and our pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions and the on-site infrastructure.

For further information, please contact Dr Tom Kober, or for project related questions Dr Martin Densing

Please submit your application online by 26 April 2020 (including addresses of referees) for the position as a PhD Student (index no. 4502-01).

Paul Scherrer Institut Human Resources Management, Nicole Schubert, 5232 Villigen PSI, Switzerland