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Field
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-edge control algorithms for the security of cyber-physical systems? Then you are the PhD candidate we are looking for! Information We invite highly motivated students with a strong background in
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applications in the media change journalism, the public sphere, civic engagement and economic competition. We will develop and test new AI-applications to help solve problems such as disinformation, algorithmic
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mathematical methods, algorithms, and applications are required. Simulators are a recognized method for architectural design explorations and the implementation of software development platforms. The goal
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AI-applications to help solve problems such as disinformation, algorithmic bias and filter bubbles. Together with our partners we will also (co)-create new ethical and legal frameworks for responsible
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new globally accessible infrastructure and new algorithms for multimodal mining of biosynthetic diversity, as well as novel lead compounds that can be taken up by consortium partners to attain concrete
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-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning algorithms that maximize the information extracted from
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algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement learning. Deep
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to ensure high predictive capability and, on the other hand, keeping the models sufficiently “compact” (i.e. algorithmically small and computationally efficient) to enable incorporation in integrated PED
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control algorithms lies a physics-based simulation model, whose accuracy largely determines the effectiveness of the control loop. Position 3 – High-fidelity simulation of the LAFP process Current
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well as collaborate with PhD candidates. You'll design experiments using our robotic platform, analyze tactile data patterns, implement real-time control algorithms, and validate performance across diverse scenarios