The fellow in this research project is required to:

• Develop and implement advanced process and energy system models for integrated, low-carbon, and net-zero energy applications.
• Conduct research on energy systems integration and sector coupling across electricity, heat, and fuels, including Power-to-X pathways (e.g., hydrogen and synthetic fuels).
• Design and apply advanced optimization and control methods, including model predictive control (MPC), data-driven approaches, and physics-informed models.
• Perform dynamic simulation and techno-economic and environmental assessment under real operating conditions and uncertainty.
• Investigate geothermal and hybrid renewable energy integration within multi-energy and process systems.
• Lead and manage research projects and work packages, ensuring the timely delivery of outputs and alignment with objectives.
• Prepare and contribute to competitive research proposals and funding applications.
• Supervise and mentor PhD, MSc, and undergraduate students.
• Collaborate with interdisciplinary teams and external partners from academia and industry.
• Disseminate research outcomes through high-impact publications, conferences, and technical reports.

Job Requirements:

• A PhD in Mechanical Engineering, Energy Engineering, Civil and Architectural Engineering, or a closely related field.
• Strong expertise in process systems engineering, energy systems integration, and thermal sciences.
• Knowledge of Power-to-X technologies, sector coupling, and sustainable energy systems.
• Experience in geothermal and hybrid renewable energy systems.
• Strong background in optimization, control, and system dynamics.
• Experience in modeling, simulation, and optimization of complex energy and process systems.
• Experience in applying AI and data-driven methods in engineering systems.
• Strong publication record and demonstrated research contributions in relevant fields.
• Proficiency in programming languages such as Python and MATLAB.
• Experience with system modeling tools such as TRNSYS, Modelica, or equivalent platforms.
• Strong analytical, problem-solving, and scientific communication skills.
• Ability to lead research activities and manage projects independently.
• Strong supervision and mentoring capabilities.
• Ability to work effectively in multidisciplinary and collaborative research environments.
• Familiarity with Information Theory (specifically entropy concepts) as applied to model confidence calibration.

We regret to inform that only shortlisted candidates will be notified.

Hiring Institution: NTU

The fellow in this research project is required to:

• Develop and implement advanced process and energy system models for integrated, low-carbon, and net-zero energy applications.
• Conduct research on energy systems integration and sector coupling across electricity, heat, and fuels, including Power-to-X pathways (e.g., hydrogen and synthetic fuels).
• Design and apply advanced optimization and control methods, including model predictive control (MPC), data-driven approaches, and physics-informed models.
• Perform dynamic simulation and techno-economic and environmental assessment under real operating conditions and uncertainty.
• Investigate geothermal and hybrid renewable energy integration within multi-energy and process systems.
• Lead and manage research projects and work packages, ensuring the timely delivery of outputs and alignment with objectives.
• Prepare and contribute to competitive research proposals and funding applications.
• Supervise and mentor PhD, MSc, and undergraduate students.
• Collaborate with interdisciplinary teams and external partners from academia and industry.
• Disseminate research outcomes through high-impact publications, conferences, and technical reports.

Job Requirements:

• A PhD in Mechanical Engineering, Energy Engineering, Civil and Architectural Engineering, or a closely related field.
• Strong expertise in process systems engineering, energy systems integration, and thermal sciences.
• Knowledge of Power-to-X technologies, sector coupling, and sustainable energy systems.
• Experience in geothermal and hybrid renewable energy systems.
• Strong background in optimization, control, and system dynamics.
• Experience in modeling, simulation, and optimization of complex energy and process systems.
• Experience in applying AI and data-driven methods in engineering systems.
• Strong publication record and demonstrated research contributions in relevant fields.
• Proficiency in programming languages such as Python and MATLAB.
• Experience with system modeling tools such as TRNSYS, Modelica, or equivalent platforms.
• Strong analytical, problem-solving, and scientific communication skills.
• Ability to lead research activities and manage projects independently.
• Strong supervision and mentoring capabilities.
• Ability to work effectively in multidisciplinary and collaborative research environments.
• Familiarity with Information Theory (specifically entropy concepts) as applied to model confidence calibration.

We regret to inform that only shortlisted candidates will be notified.

Hiring Institution: NTU