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interdisciplinary team from electrical, mechanical, and chemical engineering, as well as physics and chemistry, with the intention to bring promising new 2D materials out of the laboratory and into the market-place
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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally oriented
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around 30,000 people in nearly 15,000 households. SOEP aims to capture social change and thus handles a constant stream of new and diverse topics and tasks. Its data collection and generation adhere
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approaches across a range of model organisms to understand how and why we age. As a PhD candidate at FLI, you’ll be part of an international and interdisciplinary environment where basic science meets
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Description Are you interested in the development of future materials, the chemistry of crystalline molecular assemblies, or chemical reactions catalyzed by unique atomic arrangements? Do you prefer
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-Disciplinary Collaboration: Immerse yourself in a highly collaborative and interdisciplinary research environment, where you'll work alongside experts from fields such as engineering, data science, urban studies
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. The position is within the Math+ project "Information Flow & Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and
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environment, where you'll work alongside experts from fields such as engineering, data science, urban studies, and aerospace. Skill Development: Our extensive qualification concept goes beyond research
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corpora data correlation. Requirements: A master’s degree in Computational Linguistics, Computer Science or related fields. Solid background in Machine Learning and Natural Language Processing Experience
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strain engineering is a plus. Data analysis skills (e.g. in Python, MATLAB or similar) are a plus. Excellent communication skills in English, both written and spoken Strong motivation to work