Aktuelle Jobs im Zusammenhang mit PhD Position – New Insights from Existing PEM Water Electrolysis Data: Optimizing Data Analysis Using Machine Learning - Jülich bei Köln - Forschungszentrum Jülich GmbH


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PhD Position – New Insights from Existing PEM Water Electrolysis Data: Optimizing Data Analysis Using Machine Learning

vor 4 Monaten


Jülich bei Köln, Deutschland Forschungszentrum Jülich GmbH Vollzeit

Conducting research for a changing society: This is what drives us at Forschungs­zentrum Jülich. As a member of the Helm­holtz Asso­ciation, we aim to tackle the grand societal challenges of our time and conduct research into the possi­bilities of a digitized society, a climate-friendly energy system, and a resource-efficient economy. Work together with around 7,400 employees in one of Europe's biggest research centers and help us to shape change

This thesis will be partly conducted in two different institutes in Jülich. The Institute for Energy and Climate Research – Electrochemical Process Engineering (IEK-14) at Forschungszentrum Jülich with more than 20 years of experience in electrochemical energy conversion is at the forefront of innovative solutions for clean and sustainable energy conversion devices. PEM water electrolysis is one promising technology for supplying the growing demand for green hydrogen. At the Institute of Energy and Climate Research – Theory and Computation of Energy Materials (IEK-13), we contribute to fundamental understanding of electrochemical phenomena, development and characterization of tailored material solutions, and testing and optimization of new energy technologies. We are advancing the discovery and integration of energy materials by using AI to streamline the development workflow. This involves deep learning for materials characterization, inverse molecular design for targeted syntheses, and the development of ontologies and graph databases to enhance data utilization.

We are offering a

PhD Position – New Insights from Existing PEM Water Electrolysis Data: Optimizing Data Analysis Using Machine Learning


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