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teaching in key and rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is
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human fat cells. As a research assistant in our team, you will play a central role in developing and optimizing these gene editing strategies. This includes testing approaches such as integrase-deficient
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distributed computational pipelines and optimizing communication costs. You will also contribute to the integration and testing of the models in real D-MIMO environments, in close collaboration with a PhD
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intelligence - Data-driven and learning-based control - Decentralized decision-making and distributed optimization - Belief-space and uncertainty-aware planning - Neuro-symbolic and context-aware reasoning
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existing and creating new deep learning-based models for anomaly detection, theoretical and numerical studies of detection quality, creating new distributed computational pipelines and optimizing
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. There is growing interest in microsystems that can replicate the local physiology of tumors, providing a platform to identify and optimize therapeutic candidates. Our group specializes in developing
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disturbances (e.g., generator outages, transmission line failures, or system separations) Developing methodologies for optimally allocating these services based on the characteristics, availability, and
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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, providing a platform to identify and optimize therapeutic candidates. Our group specializes in developing technologies to assess the multicellular environment within three-dimensional microtumor models
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, testing, optimizing, benchmarking and validating custom machine learning algorithms for multi-dimensional remote sensing applications Good social skills, meaning that you enjoy collaborating with others in