Post-doc Machine Learning and Modelling of Perovskite Solar Cells

rug university groningen
  • Groningen
  • University of Groningen
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The University of Groningen is a research university with a global outlook, deeply rooted in Groningen, City of Talent. Quality has been our top priority for over four hundred years, and with success: the University is currently in or around the top 100 on several influential ranking lists.
The Faculty of Science and Engineering (FSE) is the largest faculty within the University. We offer first-rate education and research in a wide range of science and engineering disciplines, from classical disciplines such as mathematics, astronomy and mechanical engineering, to interdisciplinary fields such as artificial intelligence, pharmacy and nanoscience. Our community has an open and informal character with students and staff from around the world.

The position we offer will be embedded in the Zernike Institute for Advanced Materials. The research group Photophysics and OptoElectronics is part of the Zernike Institute for Advanced Materials in the Faculty of Mathematics and Natural Sciences of the University of Groningen. The group's main research interests lie in the use of novel semiconducting materials for optoelectronic applications and devices. The group provides a lively, internationally oriented scientific environment with excellent facilities.

We are seeking a highly motivated postdoctoral researcher to join our team working on the development of high-efficiency wide-bandgap perovskite for application in perovskite-perovskite tandem solar cells. The successful candidate will work in a collaborative environment with leading European academic and industrial partners, including the universities of Oxford and Valencia, on a large-scale European project.

The focus of the postdoc project will be on using advanced numerical simulation modeling software and machine learning techniques to quantitatively study the electrical characteristics of state-of-the-art perovskite solar cells. Specifically, the successful candidate will identify the loss mechanisms of the perovskite solar cells made and measured by the other partners through the use of extensive numerical modeling. This will involve extending our current drift-diffusion modeling software, applying it to experimental data, and using machine learning to identify trends in the data.

Applicants should have a PhD in physics, materials science, electrical engineering, or a related field. A deep understanding of device physics, numerical modeling, and computer programming is required. Experience in machine learning and data analysis is highly desirable but not essential.

The postdoc will be based at the Zernike Institute for Advanced Materials, one of the leading institutes in the field of materials science, and will be supervised by Prof. Dr Jan Anton Koster, an expert in the field of photovoltaics.

This is an exciting opportunity for a talented and ambitious researcher to join a dynamic and collaborative team working on cutting-edge research in the field of perovskite solar cells. The successful candidate will have access to state-of-the-art facilities and a supportive research environment, as well as opportunities for personal and professional development.

Ole Gmelin
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Will you become our new Post-doc Machine Learning and Modelling of Perovskite Solar Cells? Apply at University of Groningen