Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain.
The
Laboratory for Computational Engineering focuses on developing technologies that support energy transition and a sustainable society by devising novel approaches and algorithms to help research in strategic areas (porous materials science, carbon negative technologies, and renewable energy integration), employing numerical simulations to understand complex systems and processes, and solving practically relevant problems to support a sustainable and healthy society. The laboratory has an extensive experience in investigating coupled multiphysics phenomena and complex multiscale processes, as well as in developing and using innovative scientific computing techniques (including HPC, machine learning, multiscale algorithms). It also has excellent experimental infrastructures (including cutting-edge experimental fluid dynamics facilities, and various equipment to investigate processes in porous materials) that used to advance electro-optical methods and to devise machine learning methods for data analysis and control.
Your tasks
The postdoctoral researcher will work on quantum chemical (QC) modeling of amorphous materials and undercoordinated defects on oxidic surfaces. The postdoc will work in a team of scientists with diverse backgrounds and will tightly interact with experimentalists. In this project, by comparing modeling results and experiments, we aim to establish a framework to digitally accelerate the design of sustainable amorphous catalysts by integrating computational and analytical methods.
Your profile
The applicants must hold a recent PhD degree, preferably in physics, chemical engineering, materials science, or mechanical engineering. Knowledge of the theory and demonstrated proficiency with QC modeling is mandatory for this position: the candidate must have an excellent record of accomplishments and publications (for the corresponding career stage) that proves an extensive hands-on experience and the ability to autonomously work with QC codes (e.g., CP2K, Quantum Espresso, or VASP). Knowledge of machine learning algorithms and experience in dealing with real data are an asset. The candidate is a curious, passionate, and proactive individual that can autonomously advance the project, engaging in discussion with the other members of the research team.
Our offer
We offer internationally competitive conditions, optimal computational and experimental facilities, and the opportunity to work in a multidisciplinary environment where communication and interaction to create synergies and develop novel ideas are highly valued. The position is available for two years starting in fall upon mutual agreement.
We live a culture of inclusion and respect. We welcome all people who are interested in innovative, sustainable and meaningful activities - that's what counts.
Patricia
Nitzsche,
Stv. Leiterin Human Resources / Dep. Head Human Resources