Wallenberg-NTU Postdoctoral Fellow

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.