Forschungszentrum Jülich GmbH (Research Center Jülich) is one of the largest, interdisciplinary research centers in Europe. With its powerful supercomputing resources and attractive geographic location in proximity to many German and European urban centers it gives attractive opportunity for cutting edge and enjoyable research.

Computational Materials Modeling division at the Institute for Energy and Climate Research, IEK-13: Theory and Computation of Energy Materials, in Forschungszentrum Jülich, is seeking a highly motivated young researcher to perform ground-breaking, computer-based simulation of materials for electrochemical energy technologies. Green hydrogen production via water electrolysis will play a vital role in a defossilized energy economy of the future. Economically affordable Fe-doped Ni-(oxy)hydroxide (Fe:NiOOH) that operate under alkaline conditions are highly active for the oxygen evolution reaction (OER) at the anode. However, the underlying molecular mechanisms have remained elusive with contradicting scenarios being considered in the literature. With the aid of thermodynamic modeling and electronic structure calculations we have found a way to decipher some crucial aspects of composition vs. structure vs. activity relations, e.g. role of the low-spin state of Fe for the enhancement of the electrocatalytic performance of Fe:NiOOH (https://www.nature.com/articles/s41467-023-38978-5). To further deeper our insight and make a decisive move towards a computationally and AI-driven selection and design of electrocatalysts we will have to overcome the intrinsic limitations of time- and length-scales of electronic structure based atomistic simulations.

The research to be performed will enable such simulations by designing a state-of-the-art machine learning force fields and apply them in accelerated simulations on superior computational infrastructure of Forschungszentrum Jülich. A neural-network based force field (NN-FF) parameterized with first-principles reference data for the Fe:NiOOH/water interfaces under alkaline conditions will be developed and applied to reveal the kinetic pathways of the OER, the overpotential determining steps and the role of Fe as both active site and enhancer of OER activity, which are highly important for optimization of electrocatalysts. The project will be performed in partnership between IEK-13, Jülich Supercomputing Center and Utrecht University in Netherlands.

Required profile of doctoral candidate:

- Master degree/experience in computational chemistry, physics, materials science or related discipline

- Education/experience in high performance/scientific computing and ML/AI methods

- Familiarity with basics of mainstream programming languages (e.g., C/C++, Fortan90, Python)

- Interest in research on energy materials

- Good communications skills, scientific curiosity and interest in interdisciplinary research

Our offer:

- Deep and diversified expertise in theoretical electrochemistry, materials modeling and high performance computing

- World-class supercomputing infrastructure, including incomming first European Exacale supercomputer JUPITER

- Stimulating, vibrant environtment of large research center

- Open-minded and stimulating discussion culture; opportunities to develop professional skills

- Networking with leading academic and research partners

- Optimal conditions for balancing work and private/family life

- Remuneration and social benefits in accordance with the collective agreement for the public sector (TVöD-Bund)

We are looking for excellent and enthusiastic candidates! Please apply under:

Please send your application in a single pdf, including CV, to:

Dr. Piotr Kowalski ([email protected])

Head of Computational Materials Modeling division (IEK-13, Forschungszentrum Jülich GmbH)

For more information on the research group and the institute please check here:

https://www.fz-juelich.de/en/iek/iek-13/divisions-1/computational-material-modeling

https://www.fz-juelich.de/en/iek/iek-13