31 operations-"https:" "https:" "https:" "https:" "https:" scholarships at Technical University of Munich in Germany
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learn new techniques and work across disciplines is essential, as is a focus on mechanistic understanding, reaction kinetics, and analytical methods. Candidates should have very good English communication
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are available here: https://www.cs.cit.tum.de/en/prog/open-positions/ Informal inquiries are welcome at [email protected]. The position is suitable for disabled persons. Disabled applicants will be given
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. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Application We are looking forward
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for reinforced, additively manufactured concrete and other mineral materials. The professorship operates an advanced extrusion-3D concrete printing facility, and as part of the laboratory for structural
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Mathematics) . Remuneration is 100% TVL E13 according to the German public sector rates. You have the opportunity to pursue a doctoral degree (Dr. rer. nat., i.e. the "German PhD"). The primary place of work
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more about logical zonotopes: paper link: https://lnkd.in/e-avQ-2B talk link: https://lnkd.in/eYGWFKmy You will conduct original research on logical–zonotope–based methods for model checking and digital
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: ▪ Implementing physical-layer security strategies derived from theoretical work, such as wiretap codes, artificial-noise transmission, secure beamforming, physical-layer authentication, and channel-based secret
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nutrition · Enthusiasm for experimental laboratory research and analytical work · An interest in understanding the relationship between food structure, digestion and health · A structured and independent
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the field of ecophysiology, plant biology, forest growth sciences, ecohydrology, or related fields Interested in tree growth, experimentation, mechanistic modeling, and plant functioning Good quantitative
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with a strong background in mathematics, computer science, or machine learning. The work has a strong focus on developing new objectives or new architectures for medical deep learning and on new ways