PhD position in smart energy management for buildings and districts

fredag 17 dec 21

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Frist 1. februar 2022
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A large amount of energy is consumed to create comfortable built environments for people, associated with a large amount of carbon emissions. New methods and tools are needed to increase the use of renewable energy in cities. As energy systems in buildings, districts and cities are complex, energy saving and energy flexibility provision must reflect system physics for efficient energy management. Thus, this project integrates system physics in a hierarchical spatial and temporal framework, including models for energy aggregation at different levels, combing machine learning with mathematical models of known physical processes. This project aims to develop innovative smart energy management technologies and solutions for buildings and districts in cities by effectively leveraging advanced big data and mathematical modelling technologies. These include data-driven predictive models for energy dynamics characterization and energy flexibility prediction for buildings and districts; model predictive control and optimization methods for distributed energy systems; and game theory-based methods for optimization and coordination of buildings and distributed energy systems. Methods developed will be tested and showcased in living labs in Hong Kong and Shanghai.

Responsibilities and qualifications
The overall focus of the project will be data analytics, data-driven modeling, and energy flexibility characterization. Your work will involve multiple techniques in the fields of both building technologies and mathematical modeling. The tasks include data-driven characterization of energy dynamics of typical energy systems in buildings and districts; aggregation and disaggregation of energy consumption and flexibility; and model predictive control of HVAC systems.

You need the following specific qualifications

  • Knowledge of HVAC system operation in buildings
  • Skills of big data analysis and data-driven modeling
  • A background in mechanical engineering, civil engineering, electrical engineering, or other relevant fields, and experience in building automation or building energy management is preferred
  • Candidates with knowledge of time series analysis are preferred
  • Proven experience with programming, e.g., Python, R

Besides, you will take part in our teaching of BSc and MSc students in student projects and/or in ordinary courses as Teaching Assistant. 

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment
The scholarships for the PhD degree are subject to
academic approval, and the candidates will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the 
DTU's rules for the PhD education.

The assessment of the applicants will be made by the main supervisor Associate Professor Rongling Li, DTU Civil Engineering, and the co-supervisor Professor Henrik Madsen, DTU Compute.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

We expect that the project start no later than August 2022.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Associate Professor Rongling Li,

You can read more about DTU Civil Engineering at and DTU Compute at

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark

Application procedure
Your complete online application must be submitted no later than 1 February 2022 (Danish time)

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • A letter motivating the application (cover letter) with contact information of three referees
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma including official description of grading scale

* In order to obtain academic approval, a student must have an MSc grade point average of at least 8 (7-point grading scale) in addition to having received a high grade on the master's thesis (10 or 12).

DTU does not admit PhD students with a grade point average below 6 (7-point grading scale). If the student’s grade point average is between 6 and 8, aptitude for research must be demonstrated, e.g. through publication of scientific papers.

Incomplete applications will not be considered.

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 12,900 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.