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, Human-Robot Interaction, Imaging Technology, Machine Learning, Medical Informatics, Medical Robotics, Natural Language Processing, Neuroinformatics, Optimization, Physical AI, Probabilistic Models
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sizes and aspect ratios. You will investigate defect formation mechanisms, optimize process parameters, assess scalability, and contribute to the development of robust fabrication processes that enable
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real-world industrial systems. The digital twin applications will include process monitoring, estimation, analysis, optimization, and control policy development. The project requires hands-on expertise
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qualifications with a university degree (Master or equivalent) in physics, engineering or computer science Proficiency in computer vision and machine learning with Python Knowledge of X-ray physics and laboratory
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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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, or Mixed Reality to support spatial understanding, coordination, and decision-making in a given phase or AEC discipline. Seamless Digital Processes: Integrated information management from office to site
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works on increasing the efficiency of industrial systems in real-world deployment by enabling process monitoring, learning, and policy training while ensuring safety and efficiency. For this, we develop
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Boundaries. However, the current process design paradigm is too slow, labor-intensive, and fragmented between disciplines. This project will investigate optimal pathways for creating a circular industry that
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interventions with a patient’s clinical state, lesion characteristics, and multimodal biomarkers to optimize therapeutic effectiveness, across the pathway of care. This research axis is embedded in the CEREBRIS
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academic and industrial research. The topic of the PhD position sits at the crossroads of quantum computing, machine learning, and combinatorial optimization — an area where some of the most exciting and