PhD position Optimization within the Energy Transition (2.0 FTE)


Faculty of Economics and Business


University of Groningen

Since its foundation in 1614, the University of Groningen has enjoyed an international reputation as a dynamic and innovative centre of higher education offering high-quality teaching and research. Balanced study and career paths in a wide variety of disciplines encourage the approximately 32.000 students and researchers to develop their own individual talents. Belonging to the best research universities in Europe and joining forces with prestigious partner universities and networks, the University of Groningen is truly an international place of knowledge.

Faculty of Economics and Business
The Faculty of Economics and Business has an inspiring study and working environment for students and employees. International accreditation enables the Faculty to assess performance against the highest international standards. It also creates an exciting environment of continuous improvement. FEB's programmes, academic staff and research do well on various excellence ranking lists.

The Graduate School SOM of the Faculty of Economics and Business has available
Two PhD positions on the topic “Optimisation within the Energy Transition”

Job description

The two PhD positions (each 1.0 FTE) are located in the Department of Operations at the Faculty of Business and Economics, and require expertise in Operations Research. We also appreciate experience in Industrial Engineering and Data Analytics. This vacancy is part of a large, inter-disciplinary project, HEAVENN (Hydrogen Energy Applications for Valley Environments in Northern Netherlands), involving 31 public and private projects from six European countries. The consortium’s call application was supported by over 65 national and international parties from all over the world, including California, Japan and New Zealand. You will work together with dr. Evrim Ursavas, Albert Schrotenboer, prof. dr. Kees Jan Roodbergen and prof. dr. Iris Vis.

The project involves the large-scale production of green hydrogen as a feedstock for industry, storage, transportation and distribution of hydrogen and hydrogen applications in industry, the built environment and the mobility sector. We are looking for PhD candidates to investigate the opportunities and challenges related to energy transition. We focus on the situation where an integrated and systematic view of a hydrogen economy is established from the supply of renewable energy to the end use in industry, mobility and domestic use. This requires the design of an efficient hydrogen network that balances the needs and requirements of producers, distributers, controllers and end-users. The envisioned contributions of the PhD projects are:

• To contribute to the establishment of a framework for the regional scale-up of hydrogen, including
o renewable energy resource planning and allocation; electrolyser size optimization; the design of infrastructure and storage capacity optimization; design of distribution networks; high volume industrial and mobility applications; design of bunkering locations for mobility for road and water transport
• To identify the optimisation challenges of key-interest within the above-mentioned areas
• To develop appropriate Operations Research models and methods to solve the identified optimisation challenges. Examples include, but are not limited to:
o mixed integer programming based decomposition methods for hydrogen network design problems; robust optimisation for dynamic power to gas storage policies; optimal or heuristic dynamic decision making (e.g., Reinforcement Learning, Rolling Horizon heuristics) while controlling the different incentives of stakeholders in a hydrogen distribution network or hydrogen market
• To use Operations Research models and methods to assess different scenarios of future hydrogen adaptation by society using input and data provided by partners in the consortium.


• master’s degree (MSc, MA, or MPhil) in Operations Research, Applied Mathematics, Industrial Engineering or related fields
• strong academic record and demonstrated competence in quantitative modeling (i.e. Operations Research)
• a background in Energy and Logistics is appreciated, though not required
• excellence in written and verbal English
• affinity with or experience in working in business or service settings.

Conditions of employment

Contract length: 48 months.

We offer you in accordance with the Collective Labour Agreement for Dutch Universities:

• a salary of € 2,325 gross per month in the first year, up to a maximum of € 2,972 gross per month in the fourth and final year
• a full-time position (1.0 FTE) for a period of in principle four years, under the condition of a positive assessment at the end of the first year
• a holiday allowance of 8% gross annual income in May
• an 8.3% year-end bonus in December.

An assessment may be part of the procedure, consisting of psychological tests and an interview.

Job Application

Do you meet our qualification criteria? If yes, your application should include:

1. your CV
2. a motivation letter
3. a scan of your diploma including transcripts
4. proof of English proficiency
5. other relevant documents.

The documents 1-4 are compulsory and please note that incomplete application packages will not be taken into consideration.

You can submit your application until 09 February 11:59pm / before 10 February 2020 Dutch local time (CET) by means of the application form (click on "Apply" below on the advertisement on the university website

We are an equal opportunity employer and value diversity at our University. We are committed to building a diverse faculty so you are encouraged to apply. Our selection procedure follows the guidelines of the Recruitment code (NVP), and European Commission's European Code of Conduct for recruitment of researchers,

Unsolicited marketing is not appreciated.

Additional information

For additional information, please contact:

Dr Evrim Ursavas

In your application, please always include the job opening ID 220014-15

Digital application form