Develop methods that enable machine learning for energy system to reach the next level, as part of a European Innovative Training Network.
InnoCyPES, a European Innovative Training Networks (ITN), funded under H2020 Marie Skłodowska-Curie Actions (MSCA), is recruiting talented, enthusiastic, and ambitious candidates to perform excellent research and achieve breakthroughs in the field of cyber-physical energy systems. InnoCyPES targets the bottlenecks of digital transformation of the current energy system, where the ESRs are expected to study and improve various facets of digitalized and interconnected energy systems. 15 Early-Stage Researchers (ESRs) will enroll in PhD programmes in the InnoCyPES network, consisting of 7 academic and 4 industrial beneficiaries, together with 10 partner organizations.
Within the InnoCyPES network, Delft University of Technology is hiring a doctoral candidate on the subject “Enriching energy system measurements for machine learning applications.” This vacancy is only suitable for early-stage researchers that have not lived in the Netherlands for more than 12 months during the previous 3 years (see requirements).
The aim of this project is to develop methods for interpolation, imputation and augmentation of energy system measurements using a combination of machine learning and physical system knowledge. Electrical networks are used as a motivating case, tackling the following challenges:
- Different sampling rates and data dropouts. Whereas PMUs or waveform monitoring systems measure electrical properties at a rate of many kHz, smart meters may report values only once every 30 minutes. Interpolation and imputation are required to generate synchronized pseudo-observations, subject to uncertainty;
- Non-alignment of timestamps. High-end measurement devices have GPS-synchronized clocks, but that is often not the case for low-cost infrastructure;
- Limited availability of training data. Machine learning algorithms usually benefit from large training datasets, but the number of available measurements may be limited or subject to confidentiality. Deep learning approaches such as Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs) will be used to learn salient properties of data and generate virtual measurements with similar statistical properties.
The methods developed will be combined into a flexible, open-source data preprocessing library.
The position includes two scheduled secondments:
- DEPsys, Switzerland (4 months)
- University of Salento, Italy (4 months)
This is a four-year doctoral appointment. You will be jointly supervised by Dr. Simon Tindemans (assistant professor, daily supervisor) and Prof. Peter Palensky (head of group), with industrial co-supervision from Dr. Omid Alizadeh-Mousavi (DEPsys). You will be a member of the section Intelligent Electrical Power Grids in the Faculty of Electrical Engineering, Mathematics and Computer Science. You will join a larger team of researchers and students working on AI/machine learning for energy systems.
All InnoCyPES ESRs will benefit from extensive training in technical and transferrable skills, and from interdisciplinary, international and intersectoral secondment experience. You will be expected to assist in teaching activities (student supervision, labs) related to your subject area. The anticipated start date is between 1 September 2021 and 1 November 2021.
As a condition of the grant, applicants must satisfy the following conditions,
- Early-stage researchers: Applicants must be early-stage researchers, which means at the date of start, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree.
- Mobility Rule: researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of the host institute for more than 12 months in the 3 years immediately before the recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention1 are not taken into account. For international European interest organisations, international organisations, the European Commission’s Joint Research Centre (JRC) or an ‘entity created under Union law’, recruited researchers must not have spent more than 12 months in the 3 years immediately before the recruitment date at the same appointing organisation.
Essential job requirements:
- Demonstrable interest in interdisciplinary and intersectoral research, and specifically the interface between energy systems, computer science and control.
- Completed a Master’s degree or equivalent in a highly quantitative and analytical discipline (applied mathematics, physics, computer science, electrical engineering, etc.)
- Excellent academic record (grades of B or higher) and good command of English (minimum C1 or equivalent).
- Good intuition for probability and statistics, and an ability to read and critically analyse computer science/mathematics papers.
- You enjoy performing research. You are independent, self-motivated and eager to learn.
- You enjoy programming and hold your code to a high standard.
- Knowledge of measurement and control of electrical power systems.
- Experience with Python and machine learning libraries.
- Experience with collaborative software development (e.g. open source).
Conditions of employment
TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 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.
TU Delft (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.
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 three areas:
- DC Systems, Energy Conversion and Storage (DCE&S)
- Photovoltaic Materials and Devices (PVMD)
- Intelligent Electrical Power Grids (IEPG)
The Electrical Sustainable Energy Department provides expertise in each of 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. IEPG integrates new power technologies and smart controls, which interact with other systems and allow for more distributed and variable generation
For more information about this vacancy, please contact Simon Tindemans, assistant professor, email: email@example.com, tel: +31(0)15-2784487.
For information about the selection procedure, please contact Carla Jager, Secretary, IEPG group, email: firstname.lastname@example.org.
Are you interested in this vacancy? Please apply before 30-06-2021 via the application button and upload: (1) Application letter that details your motivation and fit to the job requirements, (2) curriculum vitae, and (3) qualification evidence including MSc and BSc transcripts. Incomplete applications will not be considered.
- 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.