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to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, the newly established Chair of Algorithmic and Structural Graph Theory offers a position as
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to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, thenewly established Chair of Algorithmic and Structural Graph Theory offers a position as
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
, scanning speed, layer thickness, scan strategy and subsequent heat-treatment) has a significant effect on the microstructure (grain size, alloying elements distribution, crystallographic texture), mechanical
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the necessary algorithms. You will also develop and document a graphical user interface which handles large processing tasks efficiently and uses multiprocessing and GPU acceleration where necessary. At the same
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techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics; 3-year funding to work on your doctoral project. Up to two additional positions will be funded by a DAAD
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or related fields past experience with Machine Learning algorithms and systems past experience with robot control and operation programming experience with ROS, C/C++, Python and/or PyTorch experience in
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(https://hessian.ai/). Your tasks The scientific focus of the professorship for “Ethical and Safe AI” will be on developing methods and algorithmic foundations for AI systems whose behavior is consistent
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including forecasting models to predict the expected distribution of pests on the field to landscape scale. The research is expected to make pest forecasts and link them to the existing expertise in crop
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-body positron emission tomography (PET) with magnetic resonance imaging (MRI). In conjunction with the development of algorithms, dedicated software and hardware-based simulations will be developed
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successful applicant, you will drive your own research, analyze NGS and other high-throughput data from patient cohorts and work on the development of improved NGS data analysis algorithms and design novel