Phase 2 of the SinBerBEST (SBB) program has an opening for a research engineer who will conduct research, as well as develop and deploy next-generation modeling tools for the design and operation of Modelica-based building air conditioning systems. , EnergyPlus, TRNSYS, HVACSIM+, IMF standards, etc. SBB works closely with industry to develop technologies for buildings that increase energy efficiency and improve the comfort, health and safety of building occupants. The immediate tasks of the Research Engineer will be to contribute to the research, development and implementation of an AI-enabled ACMV/HVAC and AHU control system for buildings. The candidate would also work on unconventional air conditioning approaches for Singapore. The candidate is also expected to contribute to research on model-based district cooling analysis, design and optimization.
We are looking for motivated candidates who can demonstrate excellent academic results in relevant fields and who are ready to thrive in a dynamic, multicultural and multidisciplinary research team. The successful candidate must develop and implement an AI-based prognostic model for ACMV/HVAC and AHU systems in buildings. The candidate must also be motivated, able to conduct experiments alone or in groups. The candidate should also help write research proposals and help manage research funds and deliverables.
- The candidate must perform analytical studies on the design and development of ACMV/HVAC & AHU to demonstrate energy efficiency and improve occupant comfort, health and safety in buildings.
- The candidate should be able to understand and safely implement various failure scenarios in ACMV/HVAC & AHU testbeds and simulation environments and study component level failure detection methods and systems.
- The candidate should help the team publish research articles in high-impact journals and produce invention disclosures.
- Must be able to work in a team, with government agencies and collaborators with regards to research.
- Must be able to write research proposals, assist the PI in applying for research grants, and manage research funds.
- Diploma/Masters in Electrical/Mechanical Engineering
- Able to design, analyze and perform experiments on ACMV/HVAC and AHU systems in test bench and simulation environments.
- Solid knowledge of programming languages, preferably Modelica, R, Python, C etc.,
- Knowledge of tools such as EnergyPlus, TRNSYS, HVACSIM+ would be a distinguishing factor
- Able to develop graphical user interface
- Able to work on multiple tasks and projects
- Familiar with AI/Machine learning and data analysisOpen to CDD.
- Open to CDD.
At NUS, the health and safety of our staff and students is one of our top priorities, and the COVID vaccination supports our commitment to keeping our community safe and making NUS as safe and welcoming as possible. . Many of our roles require a significant amount of physical interaction with students/staff/audience members. Even for professional roles that can be performed remotely, there will be instances where on-campus presence will be required.
Considering the health and well-being of our staff and students and to better protect everyone on campus, applicants are strongly encouraged to be fully vaccinated against COVID-19 to gain successful employment with NUS .
Location: Kent Ridge Campus
Organization: College of Design and Engineering
department : Electrical and Computer Engineering
Eligible Employee Referral: Nope
Job Application ID: 17375