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computing-based data processing and develops machine learning methods in support of quantum technologies. The team is part of flaQship , the Fraunhofer Lab for applied quantum computing Stuttgart-Heilbronn
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on quantum computing-based data processing and develops machine learning methods in support of quantum technologies. The team is part of flaQship , the Fraunhofer Lab for applied quantum computing
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energies, and sustainability. In addition, next-generation computing and quantum computing are future-oriented topics that our researchers are working on. Our research fields are in the following areas
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Programming, data analysis and visualization in Python Numerical modeling and programming for model optimization and machine-learning applications Perform material characterization of various optical glass
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position requires mastering computing tools and the successful candidate will be expected to demonstrate a strong interest and affinity for digitization and to embrace change. Duties and Responsibilities
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position requires mastering computing tools and the successful candidate will be expected to demonstrate a strong interest and affinity for digitization and to embrace change. Duties and Responsibilities
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themselves, for us and for the markets of today and tomorrow. In the area of expertise ‘IT Forensics’, we research and develop methods for the digital search for evidence in IT systems and on the
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. Applying (implementation of common ML methods such as hyperparameter optimization, binary/multi-class/multi-label classification, ensemble methods, ... Evaluation/benchmarking based on standardized
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responsibility include the following: implementation/porting of algorithms from the fields of deep learning and audio signal processing extension of methods in the field of music information retrieval, e.g. for
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using methods such as spin coating or thermal evaporation, and thereby fabricate complete solar cells yourself. You will characterize the solar cells using optoelectronic and optical methods, including