Postdoctoral researcher on modeling electrochemical systems

Decarbonization of our energy economy is paramount to combat climate change. Large scale energy storage must be deployed at a global scale to enable widespread integration of renewable energy technologies (e.g., solar and wind power) and secure grid stability. Redox flow batteries are a class of rechargeable electrochemical devices that are suited for storing megawatt-hours of electrical energy for multiple hours. However, current flow batteries are hampered by technical and economic challenges which motivates the exploration of new chemistries and reactor formats to enable transformative improvements. Specifically, engineering the electrode microstructure and surface properties is a powerful approach to enhance the performance, cost, and durability of the system. However, to date there is limited knowledge on how to deterministically design porous electrodes which results in a reduced choice of electrode materials, mostly limited to fibrous based substrates which fundamentally limit the performance of redox flow batteries. Thus, there is an urgent need to develop precisely engineered electrode materials using versatile and scalable manufacturing techniques to unlock new electrochemical systems.

FAIR-RFB (Engineered Porous Electrodes to Unlock Ultra-low Cost Fe-air Redox Flow Batteries) is an ambitious research project funded by the European Research Council (ERC Starting Grant). The main aim is to develop a low cost and long-duration energy storage system and we will focus on the fundamental science of porous electrodes to realize this goal. The postdoctoral researcher will develop new computational frameworks to accelerate porous electrode design by bridging concepts from machine learning, topology optimization, electrochemical multiscale modeling, and polymer physics. Our ultimate objective is to answer the following question: How does an 'optimal' electrode microstructure look like and what is the recipe to make it?

• PhD in Chemical Engineering, Computational Science, Mechanical Engineering, Physics, Mathematics, or a related discipline.
• Expertise in modeling electrochemical systems, machine learning, topology optimization, and porous materials is highly desired.
• We are looking for a talented, motivated, and enthusiastic researcher who is driven by fundamental and applied research in electrochemical energy technologies and wants to make a positive impact in our team and society.
• Excellent mastering of the English language.
• Leadership, supervision skills, and strong communication skills.
• We prefer candidates with a good team spirit, who like to work in an internationally oriented, social environment.

An interview and a scientific presentation are part of the selection procedure.