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Our research group focuses on the development of AI algorithms for industrial applications. The main scope of our activities is the optimization and automation of workflows and production systems
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scientific questions or develop algorithms that perform automatically some challenging tasks. This typically involves exchanging actively with collaborators and domain experts to understand the precise
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. Integrate various datasets, such as tree species annotations, climate, and topography, into deep learning algorithms. Test deep learning models (Transformers and CNNs) for optimal accuracy using large
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) or neural network-based methods. The level of the targeted problems will require further mathematical and algorithmic developments over the current state of data-driven SSM reduction. The PhD position will
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: graph neural networks, natural language processing, algorithmic learning, fault-tolerance, blockchains, consensus, cryptocurrencies, digital money, central bank digital currency, decentralized finance
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using learning-based algorithms Development of a simulation framework for stressor analysis and traffic equilibrium modeling Integration of predictive analytics and multi-agent reinforcement learning
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algorithms and AI-based solutions for data processing and validation, and provides scientific expertise for the implementation of future remote sensing missions. The team’s work bridges earth observation with
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multiphysics simulation Develop multimodal decoupling algorithms Scalable O-skin fabrication and system integration onto robots and as wearables Realtime sensory mapping in complex environments Supervise master
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based on the extracted image data. Job description Develop and apply state-of-the-art algorithms for image segmentation, feature extraction, and quantitative analysis Combine classical image processing
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on developing systems that integrate technological innovations, scientific principles, advanced mathematics, algorithms, and design in groundbreaking ways, particularly on advanced motion control. Key testbeds