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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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the use of instrumental analytical methods such as HPLC-MS, GC-MS knowledge in the preparation of plant tissues for the extraction of natural substances experience in the application of molecular biological
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: excellent, very good or good university degree (diploma, master's degree) in transport or related study programs with a solid basis in transport planning and/or data analytics Description of the PhD topic
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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modeling, optimization, and/or data analytics. Description of the PhD topic (subproject C1 - New metrics for transportation system appraisal): Transportation systems must deliver “function” (i.e
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of inorganic ions and organic matter can cause defects in electrolyser stacks, resulting in costly process disruptions. This project considers: i) development of analytical methods for the quantification
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research proposal required for application with a timetable for the four-year research project. Required equipment will be set up and further development of relevant analytical methods will follow