NT

Research Fellow (Sustainable Cooling in Tropical Megacities)

ntu
CompanyNTU Main Campus, SingaporeOnsitePosted 4 weeks ago

About the role

Research Fellow (Sustainable Cooling in Tropical Megacities) is a active engineering role at ntu in NTU Main Campus, Singapore. Open the role to review the official description and apply on the company site.

CompanyOnsite

Key Responsibilities

  • Develop models of integrated multi-energy systems , including interactions between electricity systems, cooling technologies, geothermal resources, and thermal energy storage
  • Analyse and model cooling demand profiles in urban environments and evaluate system integration strategies for sustainable cooling.
  • Develop simulation frameworks for energy system optimisation and performance analysis .
  • Apply data-driven methods and AI-assisted modelling approaches to improve modelling, forecasting, and optimisation of energy systems.
  • Perform techno-economic and environmental analysis of integrated energy systems, including CAPEX/OPEX estimation and carbon impact assessment.
  • Evaluate system scenarios and support the development of decision frameworks for sustainable cooling and energy system planning .
  • Collaborate with international research partners , including leading Danish universities, on advanced modelling of energy systems and cooling technologies.
  • Prepare technical reports, scientific publications, and presentations for project stakeholders and research dissemination.

Requirements

  • PhD in Mechanical Engineering, Energy Engineering, Chemical Engineering, Applied Physics, or a closely related discipline.
  • Technical Competencies
  • Strong background in energy systems modelling and simulation , particularly integrated or multi-energy systems.
  • , cooling technologies, geothermal systems, or district energy systems .
  • -economic analysis of energy systems.
  • Proficiency in scientific computing environments such as Python, MATLAB, Julia, or Modelica .
  • -driven modelling, machine learning, or AI applications in energy systems is an advantage.
  • Familiarity with modelling of energy networks, district cooling systems, or integrated urban energy infrastructures is desirable.
  • We regret to inform that only shortlisted candidates will be notified.
  • Hiring Institution: NTU