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PhD Position - Organic Electrosynthesis: monitoring of reaction transients with real-time techniques
for selected electro-organic transformation in detail: Design, validation and verification of online and offline analytical methods Design, synthesis, and characterization of catalytic materials Utilization
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-analytic methods (e.g., meta-analytic structural equation modeling) We are looking for a motivated researcher who is eager to contribute to a vibrant and growing field with strong societal relevance. Your
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practical experience in at least one programming language (preferably Python) Ideally, some practical experience in material characterization methods Structured and analytical thinking as well as a systematic
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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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Frankfurt School of Finance & Management • | Frankfurt am Main, Hessen | Germany | about 7 hours ago
, Finance, and Management. You will develop strong analytical skills, publish in top journals, and join a global academic network. This fully-funded programme includes advanced courses, close faculty support
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. Qualifications The applicants should possess: An excellent or very-good university degree in economics, business studies, agricultural sciences with a focus in economics, or related disciplines Strong analytical
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material characterization methods Structured and analytical thinking as well as a systematic, careful, independent, and reliable working method Strong cooperation and communication skills and the ability
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Areas of study Neuroscience, Physics, Applied Computer Science, Bioinformatics, Computer Science, Engineering Informatics, Medical Informatics, Chemistry, Analytical Chemistry, Inorganic Chemistry
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like PyTorch or TensorFlow Strong analytical and communication skills, creativity, and the ability to work independently while collaborating in a team-oriented environment Our Offer: We work on the very
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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