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or they are working on projects requiring access to the Berlin research institutions. For almost an entire year, they are given the opportunity to participate in Berlin's scientific life and to get to know the culture
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sensors and apply them to novel applications. Technically, your work will involve the design and construction of optics and electronics, clean room fabrication and software development, as well as theory
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for students. Requirements We require for the position the following: A Ph.D. in the field of Applied Mathematics, Computer Science, Computational Science and Engineering, or similar. Knowledge of numerics as
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Euro / year + benefits). 3D Semantic Scene Understanding: The world around us exists spatially in 3D, and it is crucial to understand real-world scenes in 3D to enable virtual or robotic interactions
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the robotics community. Requirements Please consider applying if you have a strong background in robotics, mechatronics, and control engineering. We especially seek individuals with excellent background in
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Euro / year + benefits). 3D Semantic Scene Understanding: The world around us exists spatially in 3D, and it is crucial to understand real-world scenes in 3D to enable virtual or robotic interactions
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interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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computer science department is the Top-1 ranked computer science department in Germany. Our culture is highly international with over 40% international students in the MA program. The visual computing lab embraces
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) and present your work at top conferences and journals in our field. Candidates should have completed their Master/Diploma studies in Computer Science, Mathematics, Mechatronics, Electrical Engineering
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responsibilities: - implement, develop and extend methods for processing and analyzing single-cell RNAseq and protein profiles (CyTOF) - develop methods for second level analyses e.g. interaction networks