70 polymer-material-simulation-research PhD positions at Technical University of Munich
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that explores biotechnological solutions to the environmental, ethical, and sustainability challenges of conventional animal agriculture. Our research focus is the development of alternative proteins
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-disciplinary research unit, which provide bioengineering solutions to urgent societal needs. CBI scientists develop next-generation imaging and sensing methods to measure previously inaccessible properties
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21.10.2021, Wissenschaftliches Personal PhD Position at TUM Department of Science, Technology & Society (65% for 3 years) within a DFG-funded research project led by Dr. Susanne Koch and affiliated
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with the possibility of renewal (TV-L E13 75%) in a highly motivated team combing on equal footing experimental and theoretical research. As an equal opportunity and affirmative action employer, TUM
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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially
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of extension (TV-L E13 75%) in a highly motivated team combing on equal footing experimental and theoretical research. Professional career development complementing your scientific research is offered via TUM
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paid PhD position in the area of Natural Language Processing starting as soon as possible. Your responsibilities Research & development projects in the area of NLU and NLG Contribution to teaching on
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paid PhD position in the area of Natural Language Processing starting as soon as possible. Your responsibilities Research & development projects in the area of Software Engineering. Possible areas
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include: Literature research Designing, implementing, and evaluating novel machine learning approaches to retrieve buildings in 3D, building settlement types, and distribution of construction sites at very
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. We are looking for candidates with research interest in the theoretical analysis of algorithms. In particular, the candidate shall work on appproximation algorithms for scheduling problems in parallel