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in Earth Observation develops innovative methods for information extraction from remote sensing data in close cooperation with the Department EO Data Science of the Remote Sensing Technology Institute
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(e.g. econometrics, statistics) interest in natural resources, agriculture or the general food system and related technology a high motivation and the ability to work independently with a strong team
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extraction from remote sensing data in close cooperation with the Department EO Data Science of the Remote Sensing Technology Institute of the German Aerospace Center (DLR). For this international, exciting
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08.09.2021, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13
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) for performing fundamental research in the frame of the project AI-CHECK funded by the International Graduate School of Science and Engineering (IGSSE). The candidate has the opportunity to pursue a doctoral
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well as knowledge representation and inference. In the research project DrawOn, new technologies for analyzing 2D digital drawings and reconstructing 3D building models will be developed. The goal of this project is
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matter physics, biomedical/material engineering or a related discipline. You have a strong background in data analysis and image processing. You enjoy working in interdisciplinary and international teams
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of approximation and online algorithms, algorithmic game theory or algorithm engineering. The position is paid according to the German public salary scale TVL-13 and provides a competitive salary with standard
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or comparable degree in physics, biology, bioengineering, material engineering or a related discipline. You have experimental experience in cell/tissue culture, microfluidics, or a related discipline. You enjoy
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, adversarial attacks, and Bayesian neural networks. Excellent analytical, technical, and problem-solving skills Excellent programming skills in Python and PyTorch including fundamental software engineering