Postdoctoral Researcher Position in Energy Transition Modeling
Institution: University of Zagreb, Croatia, Faculty of Mechanical Engineering and Naval Architecture
Duration: 20 months (until November 30, 2026)
Field: Technical Sciences – Mechanical Engineering or Electrical Engineering
Project: AI-NPT (Croatian Science Foundation)
About the Project
The AI-NPT project focuses on the challenges of modeling the energy transition, particularly the electrification and decarbonization of hard-to-decarbonize sectors such as industry and transport. The proposed approach moves away from traditional perfect-foresight models towards a rolling-horizon framework. This method enables:
- A dynamic response to various future conditions and system states.
- Reduced computational requirements and data intensity compared to existing models, which have proven to be limiting.
By offering greater flexibility, this approach allows for better management of rapid changes in resource availability and unexpected events, such as extreme weather conditions, while adapting to hardware constraints.
The project leverages artificial intelligence (AI), specifically neural networks trained on historical data relevant to expected conditions in the modeled scenarios. It also integrates uncertainty modeling for future data and curve values, addressing limitations in rolling-horizon methods in meeting comprehensive constraints.
Further, the research emphasizes the integration of multiple energy vectors and the use of AI for preprocessing input data. This enables, for example, demand curve aggregation across different zones and production units in alignment with computational capabilities. The geographical placement of components in e-fuel production is considered, taking into account multi-zone modeling.
Expected Outcomes
The AI-NPT project aims to enhance:
- The adaptability of energy systems to changing conditions.
- The reliable integration of renewable energy sources.
- Long-term strategic energy planning capabilities.
- The precision of energy models to better reflect the complexities of modern energy systems.
Your Role
As a Postdoctoral Researcher, you will:
- Develop and implement AI-based methodologies for energy transition modeling.
- Work on the integration of rolling-horizon optimization and uncertainty modeling.
- Contribute to multi-energy vector system modeling.
- Conduct computational simulations and analyze results.
- Collaborate with interdisciplinary research teams.
- Publish research findings in high-impact journals.
Required Qualifications
- PhD in Mechanical Engineering, Electrical Engineering, Energy Systems, or a related field.
- Strong background in energy system modeling, AI applications, or computational optimization.
- Experience with programming languages such as Python, MATLAB, or similar.
- Knowledge of neural networks and machine learning techniques is an advantage.
- Ability to work independently and as part of a team.
- Excellent command of English (written and spoken).
Application Process
Interested candidates should submit the following:
- Curriculum Vitae (CV)
- Cover Letter detailing relevant experience and motivation
- List of Publications
- Contact Information for Two References
Deadline for applications: February 7, 2025
How to apply: Send your application to Dr. Antun Pfeifer at antun.pfeifer@fsb.unizg.hr. Mentor of the researcher will be Prof. Neven Duić.
Join us in advancing cutting-edge research in AI-driven energy transition modeling!