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PhD Position in Reinforcement Learning for Autonomous Building Energy Management, Denmark

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PhD Position in Reinforcement Learning for Autonomous Building Energy Management, Denmark
от Роман Станиславович Самарев - Воскресенье, 1 Сентябрь 2019, 22:53

We invite highly motivated candidates to apply for the PhD position in Reinforcement Learning for Autonomous Building Energy Management. This is a 3-year scholarship funded by Nordic five Tech. Alliance. The PhD student will stay for two years in the Energy System Analysis Research Group at the Department of Management of the Technical University of Denmark (DTU) and for one year at the Department of Manufacturing and Civil Engineering of the Norwegian University of Science and Technology (NTNU). The student will be enrolled at both universities and can be awarded a double doctorate for successful defence.

The energy consumption of buildings accounts for about 40% of the total global energy consumption. It is therefore essential to find innovative ways to reduce and optimise the energy. Today???s prevalence of digitasiation systems make it possible to use sensor technologies, communications and advanced control algorithms to optimise energy utilization, e.g, monitoring and controlling smart home devices to reduce energy consumption and costs. However, the main challenge is how to use the modern digital technologies to achieve intelligent energy management for autonomous buildings.

*Responsibilities and tasks*

The objective of this project is to develop theory, algorithms, and applications that can be used for smart building energy optimisation. The tasks involve investigation of the limitation of the current energy systems, the use of data-driven approaches for energy optimization, and the development of controlling systems. The PhD student will closely collaborate with industry partners of related projects, and other researchers. 

The responsibilities and tasks associated with the position include:
- Active participation in the research environments at DTU;
- Develop models, algorithms, and methods;
- Present research results at project meetings, and international conferences/workshops;
- Publish research results in peer-reviewed scientific journals/conference proceedings.


The ideal candidate should be holding a Master's degree in Engineering, Applied Mathematics, Computer Science or related fields with experience in data mining, machine and deep learning, and in particular reinforcement learning. The successful candidate has strong analytical and problem-solving skills, is proactive, self-motivated with critical thinking. Strong programming skills are required, preferably in Python or R. Fluent English speaking and strong paper writing skills are mandatory. You enjoy working in an international environment, solving practical problems, and collaborating with industrial project partners.

*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.

*Work location*
The place of work is Energy System Analysis Group, Sustainability Division,  Department of Technology, Management and Economics, Produktionstorvet 426, 2800 Kgs. Lyngby, Denmark. 

*Appointment time*
The academic approval of application is 3 October 2019 or as soon as possible thereafter.

Senior Researcher Xiufeng Liu, xiuli@dtu.dk