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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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the Institute of Physical Chemistry in Warsaw and Stuttgart University. Your Profile: You are an enthusiastic and motivated researcher You have a Masters degree and a PhD in physics, chemistry, engineering or
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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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information from experiment data Evaluation and development of specialized and/or interpretable machine learning approaches for the domain of materials science, physics, microscopy Incorporation of machine
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of soft- and hardware infrastructure Close collaboration with automation experts, data and material scientists to improve and use a fast and reliable electrochemical testing process Your Profile: Master
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: Very good performance in your Master`s degree in the fields of energy technology, mechanical engineering, materials science, civil engineering, industrial engineering, physics, resource management
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masters degree and subsequent Ph.D. degree in Computer Science, Mathematics, Physics Engineering or in a similar field. Alternatively an excellent masters degree with professional experience Very good
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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
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to educational events, such as university lectures, JSC courses and hackathons. Your Profile: Excellent Master in Computer Science, Mathematics, or Physical Science, Very good knowledge and proven skills with
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creating better science through pragmatic solutions. For this you will bring: University degree (Master, Diploma or equivalent) in Material Science or other adjacent fields (e.g. Physics, Chemistry