Electrification is one of the most promising strategies to decarbonize the energy sector. The electricity sector then is key to decarbonize other sectors, such as gas, heat and mobility. In this project we aim to build a model for deciding optimal investment and operation strategies for the energy system, which includes the electricity system and the coupling with green gas (H2) and heat.

The main objective for this PhD student is to develop novel techniques in the intersection of machine learning and optimization to find the right level of modelling detail, balancing accuracy and computability.

This PhD position is part of a larger research project – Next Generation Sector Coupling Models for Optimal Investments and Operation (NextGenOpt) – which is funded by the Dutch Research Council (NWO) within the Energy System Integration, Towards Futureproof, Affordable and Reliable Energy Systems (ESI-FAR) call. Accordingly, the candidate will be embedded in an interdisciplinary team consisting of engineers, computer scientists, and mathematicians from TNO, Utrecht University, TU Delft, and industry partners. The candidate will closely cooperate with the other project team members and spend part of the research time at TNO (flexible stay).

Responsibilities:

• Perform scientific research in the area of combinatorial optimisation and machine learning.
• Implement and evaluate research prototypes.
• Write and publish scientific reports at international venues, e.g., conferences and journals.
• Present results at international conferences
• Collaborate with domain experts.
• Participate in activities of the research group.

The PhD student will be supervised by Dr. Mathijs de Weerdt from the Algorithmics research group, Prof.Dr. Karen Aardal from the Optimization group from TU Delft, and by Dr. German Morales-Espana from TNO.

To qualify for this position you must have:

• completed a relevant MSc degree in Artificial Intelligence, Computer Science, or Mathematics,
• demonstrated competences in one or more of these categories: combinatorial optimization, machine learning, statistics, algorithm design, operations research,
• demonstrated experience in programming in at least one of the following programming languages: Python, Java, C/C++,
• demonstrated experience or interests in algebraic modelling languages, such as Julia, GAMS or AIMMS,
• a proven record and interest in further developing your modelling, programming and analytical skills,
• strong affinity and enthusiasm for state-of-the-art AI, algorithmic and optimization approaches, and in applying these to support decisions regarding the energy transition,
• excellent critical and analytical thinking skills,
• an affinity with teaching and guiding students,
• proficiency in expressing yourself verbally and in writing in English,
• the ability to work in a team and take initiative,

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Fixed-term contract: 4 years.

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2443 per month in the first year to € 3122 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

Delft University of Technology

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.