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National University of Singapore

Postdoctoral Research Fellow in Flexible and Resilient Energy Systems National University of Singapore in Singapore

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Country flag

Country

Singapore

University

National University of Singapore

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Civil Engineering
Energy Engineering
Digital Twin Technology
Optimisation
Power System
Control System
Distributed Energy
Renewable Energy Systems

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About this position

The Building Informatics and Operations Research (BIOR) Lab at the National University of Singapore is recruiting two Postdoctoral Research Fellows in flexible and resilient energy systems. The fellows will work with Assistant Professor Maomao Hu in the Department of the Built Environment, College of Design and Engineering, at the Kent Ridge Campus in Singapore.

The research focuses on modeling, aggregating, and controlling distributed energy resources (DERs) to improve energy flexibility and grid resilience. Research areas include photovoltaic systems, electric vehicles, battery energy storage systems, flexible building loads, power systems, building energy systems, optimization, control, learning, energy scheduling, and dispatch.

Responsibilities include characterizing DER flexibility, developing scalable flexibility envelopes for heterogeneous resources, formulating optimization problems, creating coordination algorithms, and integrating computational models into a high-fidelity digital twin platform. Fellows will validate models and algorithms using operational data and field-test results, publish in high-impact journals, present at conferences and seminars, and collaborate with postdoctoral researchers, PhD students, research assistants, and the Centre for Digital Building Technology.

Applicants need a PhD in Electrical, Mechanical, Civil, Architectural Engineering, or a related field, with relevant training in optimization, control, and learning. Experience with energy-system modeling, large-scale optimization, programming in Python, R, or MATLAB, and interdisciplinary research collaboration is expected. Distribution-network simulation, mixed-integer optimization, digital twins, and hybrid quantum-classical optimization are advantageous.

To apply, submit a CV and a cover letter explaining your research interests and the relevance of your background through the online NUS application portal. Applications remain under consideration until the positions are filled. Only shortlisted applicants will be contacted.

Funding details

Available

What's required

Applicants must hold a PhD in Electrical, Mechanical, Civil, Architectural Engineering, or a related field, with sufficient training in optimization, control, and learning. Required experience includes modeling and analyzing power systems, building energy systems, or distributed energy resources such as photovoltaic systems, electric vehicles, and battery storage; applying optimization, control, and learning to large-scale energy systems; statistical fundamentals; and programming in Python, R, or MATLAB. Strong oral and written communication, technical publication and presentation skills, and experience collaborating in diverse interdisciplinary research teams are required. Experience with distribution-network simulation, large-scale mixed-integer optimization, and digital twins is advantageous; familiarity with hybrid quantum-classical optimization is desirable.

How to apply

Submit a curriculum vitae and a cover letter describing your research interests and the relevance of your background through the NUS online application portal. Applications are considered until the positions are filled; enquiries may be sent to [email protected].

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