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control, state estimation, and path planning algorithms for single and multi-agent robotic systems (UAVs). develop and train AI models for practical applications such as real-time object detection and
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group focuses on developing strategies and algorithms to quantity biologic effects of particle radiation based on underlying physics, biology and physiology. Within the BMFTR funded project “BIOMICRO
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detectors (Partial) automation of detector characterization for more efficient analysis Algorithm development: Development of a correction method based on information field theory for atmospheric image
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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learning (ML) methods—including surrogate modelling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor
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of the novel methods created within our research group. Your primary tasks will include: - Assisting in the research taking place in our group. - Collaborating with our researchers to translate new algorithms
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you will do Driving innovative AI research through the development and implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine
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) simulations and offer time-saving benefits. We are looking for a dedicated and motivated student to assist us in implementing a novel Graph Neural Network based algorithm that can act as surrogate for FEM and
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Iterative Algorithms: Optimization and Control.” About the Project The focus of the project is the analysis of iterative algorithms arising from time discretizations of nonlinear evolutions of various kinds
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable