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Field
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require the design of architectures suitable for real-life problems. Moreover, appropriate mathematical methods, algorithms, and applications are required. Simulators are a recognized method for
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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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for Artificial Intelligence are set to launch in the fall of 2025. These centers will foster interdisciplinary collaboration among researchers to address societal challenges, understand the impact of AI, develop
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, in partnership with major industry players (Les Éleveurs de porcs du Québec, Olymel, and CDPQ) and MAPAQ. PhD Objectives: This 4-year PhD project aims to develop and validate robust Computer vision
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. While the chosen design has a significant effect on the most important aspects of users’ experience, the algorithms, and thus the supply decisions, are based on users’ preferences. This PhD position
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new paradigm in the design, testing, and validation of Electronic Control Units (ECUs) for Connected and Autonomous Vehicles. By developing high-fidelity Digital Twins (DTs) that combine functional
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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and innovation catalyst, in this exciting project, you will develop novel algorithms to monitor and analyse workers' movements, detect harmful movement patterns, and implement simple intervention
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data Design algorithms for correlating low-level events into process-level attack models Contribute to joint framework development with TU/e on continual learning Collaborate with industry partners