PhD Position Statistical surrogate Models of Flexible Energy Systems

Energy system models are computationally demanding. To speed them up, we need advanced algorithms and open-source implementations. Join us to accelerate the energy transition!

Delft University of Technology (TU Delft) is hiring a doctoral candidate (4 years) on the subject of “statistical surrogate models of flexible energy systems”.

Numerical models are at the core of the successful operation of sustainable energy systems: models are used to forecast renewable energy production and energy demand, to anticipate the impact of severe weather, or to invest in large scale batteries to overcome lulls in wind production. Ideally, such models are all-encompassing, covering time scales from seconds to years, length scales from streets to continents, and common days as well as once-in-a-decade events. However, computational limitations mean that real-world models always balance accuracy, scope, and computational requirements.

The aim of this PhD project to drastically speed up energy system models by embedding the training and use of machine-learned surrogate models within the model run. It will be focused on the common “scenario averaging” design pattern, which appears for example when (1) averaging over many possible futures, or (2) aggregating the behaviour of many users.

We are looking for a mathematically-minded researcher who takes a principled approach to understanding data-driven methods, and can translate beautiful ideas to efficient code. Your tasks will include:

• Developing a modular approach to efficiently represent scenario-averaging in an energy system model, combining various methodological innovations (active learning, machine learning, multifidelity modelling).
• Calculate and propagate principled uncertainty estimates.
• Encapsulate the approach in a model-agnostic open-source wrapper that can be used with existing tools and libraries.

The position is part of the MuESSLi project that aims to develop smart links between models to improve the speed, accuracy and scope of energy system models. The project is run under the umbrella of the CRESYM association, a public-private non-profit association that fosters the transparent development of open-source tools for the future energy system. Within the project, you will collaborate with other PhD students from TU Delft, the Technical University of Denmark (DTU; Copenhagen), and Comillas Pontifical University (Madrid) and you will regularly interact with project sponsors RTE, TotalEnergies One Tech and GRTgaz. This project offers excellent opportunities to work in a dynamic team consisting of experts from academia and industry.

We would like the successful candidate to start as soon as possible, but flexibility exists for suitable candidates

• An MSc degree (completed at the start date) in a discipline that combines modelling and algorithmic thinking (e.g. Data Science, Artificial Intelligence, Systems & Control, (Applied) Mathematics, Physics, Operations Research). Holders of other degrees are encouraged to apply with an explanation of how comparable skills were obtained.
• Demonstrable knowledge of machine learning methods, probability & (computational) statistics.
• An excellent academic record (typical grades of 8+ (Dutch) or A).
• Excellent English skills. Holders of an MSc degree that was obtained outside the Netherlands are required to demonstrate this with a TOEFL score of 100 (min. 21 for each section) or IELTS of 7.0 (min. 6.5 for each section). Limited exceptions apply: see https://www.tudelft.nl/en/education/programmes/phd/phd-admission
• A good intuition for probability and statistics and an ability to read and critically analyse papers in the mathematics/computer science domain.
• You enjoy programming and strive to write code to a high standard.
• An affinity with the energy transition and its technical underpinnings (operation and planning of energy infrastructure).
• You like working in a multidisciplinary environment. 

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.

About the department

The research in the Department of Electrical Sustainable Energy is inspired by the technical, scientific, and societal challenges originating from the transition towards a more sustainable society and focuses on four areas:

• DC Systems, Energy Conversion and Storage (DCE&S)
• Photovoltaic Materials and Devices (PVMD)
• Intelligent Electrical Power Grids (IEPG)
• High Voltage Technologies (HVT)

The Electrical Sustainable Energy Department provides expertise in these areas throughout the entire energy system chain. The department owns a large ESP Laboratory assembling High Voltage testing, DC Grids testing environment, and large RTDS that is actively used for real-time simulation of future electrical power systems, AC and DC protection and wide-area monitoring and protection.

The Intelligent Electrical Power Grid (IEPG) group, headed by Professor Peter Palensky, works on the future of our power system. The goal is to generate, transmit and use electrical energy in a highly reliable, efficient, stable, clean, affordable, and safe way.

Your PhD supervisor will be Dr. Simon Tindemans, supported by Dr. Milos Cvetkovic. You will be a member of the Intelligent Electrical Power Grids research group, which is part of the Electrical Sustainable Department (ESE) within the Faculty of Electrical Engineering, Mathematics, and Computer Science.

For more information about this vacancy, please contact Dr. Simon Tindemans at [email protected].

For more information regarding the recruitment process you can contact: Brenda Reyes at [email protected].

Are you interested in this vacancy?

Please submit all of the following:

• A cover letter that details your motivation and fit to the job requirements;
• an up-to-date CV/resume;
• list of grades for all post-secondary education (BSc, MSc, …);
• Sample of technical writing (preferably MSc thesis or (draft) paper.

Incomplete applications will not be considered.

The deadline for applications is  31 January 2024 (23:59 CET). After an initial screening, shortlisted candidates will receive an invitation for an online interview, foreseen at the start of February. 

Also note:

• 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.