Wallenberg-NTU Postdoctoral Fellow

About the role

The Wallenberg-NTU Postdoctoral Fellowship brings outstanding young researchers who have graduated from a Swedish university to NTU for two years of postdoctoral research and study. Fellows take part in the broad range of interdisciplinary activities and programs that characterise NTU's approach to research and education.

Key responsibilities

• Develop and implement advanced process and energy system models for integrated, low-carbon and net-zero energy applications.
• Research energy systems integration and sector coupling across electricity, heat and fuels, including Power-to-X pathways such as hydrogen and synthetic fuels.
• Apply advanced optimisation and control methods, including model predictive control (MPC), data-driven approaches and physics-informed models.
• Perform dynamic simulation and techno-economic and environmental assessments 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, delivering outputs on time and aligned 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 results through high-impact publications, conferences and technical reports.

Required profile

• 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 publication record and demonstrated research contributions.
• Ability to lead research and manage projects independently, and to supervise and mentor students.

Required skills

• Optimisation, control and system dynamics; modelling, simulation and optimisation of complex energy and process systems.
• Application of AI and data-driven methods in engineering systems.
• Programming in Python and MATLAB.
• System modelling tools such as TRNSYS, Modelica or equivalent.
• Familiarity with information theory (entropy concepts) applied to model confidence calibration.