The Wallenberg-NTU Postdoctoral Fellowship is to bring outstanding young researchers, who have graduated from a Swedish university, to NTU for two years of postdoctoral research and studies. The Postdoctoral Fellows are given the opportunity to participate in a broad range of interdisciplinary activities and programs that characterize NTU’s approach to research and education.

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.