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and develops a wide range of topics related to chemical hydrogen storage along the entire process chain. We place a particular emphasis on LOHC technology, addressing issues across different scales. Our
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the standardization and harmonization of data across platforms. Work with large language models (LLM) and deep learning algorithms to drive the inverse design of materials and uncover new physical and chemical
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H2 profiles in collaboration with our modeling department Your Profile: MSc in meteorology, physics, chemistry, environmental sciences or a related field with good final grade (German system equivalent
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Engineering or Chemistry, Physics or Informatics Experience with experimental work and characterization techniques Demonstrated experience in programming, particularly in Python, with a robust understanding of
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the overall design Your Profile: Master’s degree in the field of natural sciences, engineering, or a related field of study Knowledge of energy process engineering is an advantage Huge interest in energy