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for and barriers against more sustainable approaches. The successful candidate will have strong empirical and analytical skills in the study of science and technology while also having an interest in and
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biomolecular research, bioinformatics, and high-performance analytical technologies to explore the complex interactions between the human organism and food components. To strengthen our research group Food
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to identify true performance-relevant thresholds. The outcomes will include identification of excipient classes and compositional ranges that do not affect performance, development of validated analytical
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Investigator (PI) Prof. Newig, one postdoctoral researcher, and four doctoral researchers, each focusing on one analytical stream: (1) sustainability performance, (2) democracy, justice, legitimacy, (3) global
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., BET, SEM, DSC) and analytical techniques (e.g., HPLC, GC) is an advantage. Analytical thinking, strong organizational skills, and the ability to work independently. Excellent written and verbal
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willingness to expand into population and ecological genomics is essential Structured, analytical thinking and a systematic, careful working method Enthusiasm for interdisciplinary collaboration with
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additive manufacturing, materials, and resource issues Analytical thinking and interest in systemic issues Basic knowledge of quantitative methods, data analysis, or modeling is an advantage Very good
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partial differential equations, optimization methods, or model-based control concepts is an advantage. You work independently and analytically and are interested in interdisciplinary research
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-level B2 . demonstrate the ability to work independently and manage time effectively. show team spirit. possess a collaborative mindset and strong communication skills. exhibit analytical thinking and
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04.03.2026, Academic staff The Professorship for Learning Analytics (LEAPS) at the TUM School of Social Sciences and Technology, Technical University of Munich, is seeking a Research Associate