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Your Job: The department of Electrocatalytic Interface Engineering, headed by Prof. Dr.-Ing. Simon Thiele, focuses on the development, characterization and testing of electrochemical systems from
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on the following tasks with either with a stronger model-development or application focus: Design knowledge-graph-augmented transformers and retrieval-augmented generation (RAG) pipelines that enable
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research together with cutting-edge materials science and physics. Depending on your background you will work collaboratively on the following tasks with either with a stronger model-development or
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
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slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is the development of meta-optimization techniques that can automatically search
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain
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Your Job: As a PhD candidate you will develop and deploy an artificial intelligence (AI) driven approach to streamline high-throughput experimentation (IMD-3: Institute of Energy Materials and
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, your work will contribute to establishing a fundamental understanding of the mechanical properties and microstructure of newly developed advanced ceramic materials for solid oxide electrolyzer cells