PhD Position Markov Decision Process for Power System Topological Actions

Challenge: Transforming the conventional carbon-intensive energy use

Change: AI to turn data into knowledge for efficient systems

Impact: Boosting the sustainable, fair and reliable energy transition

TU Delft is a top tier university and is exceedingly active in the field of Artificial Intelligence (AI) with a strong expertise in energy systems. Energy systems are the backbone of our modern society, but are becoming increasingly complex and challenging to operate as renewable energy, heating and transport sectors are integrated into the system. It’s crucially important that energy systems are sustainable, reliable and effective, now and in the future. TU Delft’s research investigates how the new area of data-driven and scientific computing can contribute to managing energy systems.

We combine ground-breaking machine learning with the reliable theory of the physical energy system. The area of data-driven scientific computing promises to combine statistics, time-frequency analysis, low-dimensional model reductions, and other techniques to extract information from data. With machine learning, we make such information useful for the management of complex energy systems. For example, it is possible to use neural networks to model differential equations that describe dynamics, and for predicting extreme, rare events. Together, the Inteligent Eletrical Power Grids research section, the Delft AI Energy Lab, and Control Rom of the Future Technology Center have currently a team of 30+ researchers investigating data-driven scientific modelling for their applicability to complex energy systems. There, you will work closely with Associate Prof Dr. Alexander Stefanov and Assistant Prof Dr. Jochen Cremer. You will extend the team and integrate your own ambitious research program within our research visions. Our PhD projects focus on assembling methods from data-driven scientific computing to build full workflows for the application to energy system problems.

As part of your 4-year PhD project you will focus on the theme of decision support for real-time topology reconfigurations in time-varying electricity systems. Along with your colleagues, you will work on real-time decision making tools that improve the system’s operating condition, and extract physical information to enhance machine learning workflows. You will investigate such workflows with a focus on the impacts on large-scale, time-sequential scheduling problems for congestion management. You will discover the dependencies across the time domain using a principled approach, and research ways to optimally decompose the problem. You will define this problem as a markov decision process, learn decisions through reinforcement that remain valid in the real electricity grid. Considering modelling errors you will develop methods to certify such a workflow, making it deployable for real-time congestion management in the Control Room of the Future (CRoF).    

• An MSc degree in either Machine Learning, Robotics, Control Systems, Operations Research or in Power/Energy Systems, Electrical Engineering, etc.
• Demonstrated competences in one or more of these categories: AI, computer/data science, machine learning, energy system modelling, dynamic systems, power systems or another relevant field.
• An affinity with teaching and guiding students
• A proven record and interest in further developing your modelling, programming, analytical and scientific writing skills
• An affinity with energy and power systems, with net-zero carbon targets, technical challenges
• The minimum requirement of a TOEFL score of 100 IELTS of 7.0 per sub-skill (writing, reading, listening, speaking) applies to all PhD candidates.
• The ability to work in a team, take the initiative, be results-oriented and systematic

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 .

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 € 2770 per month in the first year to € 3539 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 a monthly work costs contribution. Flexible work schedules can be arranged. 

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme  for partners and they organise events to expand your (social) network.

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 as one of our core values  and we actively engage  to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 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.

For information about this vacancy and the selection procedure, please contact Jochen Cremer, Assistant Professor, email: [email protected]; for questions related to the recruitment process please contact Brenda Reyes [email protected].

Are you interested in this vacancy? Please apply before August 15, 2024 via the application button and Submit the following in three pdf files: (pdf 1) 1-page Motivation letter and your CV; (pdf 2) a (part of your) M.Sc. thesis or a paper that you have written, in which you demonstrate your writing skills, (pdf 3) your MSc and BSc transcripts of grades and courses taken.

Please highlight in your motivation letter and/or CV examples of projects and achievements that demonstrate your relevant competences.      

• A pre-employment screening can be part of the selection procedure.
• You can apply online. We will not process applications sent by email and/or post.
• Please do not contact us for unsolicited services.