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the Computer Engineering group. Curious to learn more about the project, and perhaps our group? Feel free to browse our webpages: About our department: QCE department . About our group: Computer Engineering Lab
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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with machine learning. Self-Driving Laboratories (SDLs) are emerging research environments where experiments are planned, executed, and analyzed in closed-loop workflows that combine automated
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the response model from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques
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, neuroimaging and clinical psychiatry, with direct clinical impact. Your main activities are: analyzing and integrating multimodal MRI data for biotype identification; applying machine learning and advanced
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, particularly integer programming, e.g., vehicle routing and packing problems and heuristics; simulation; data-driven modelling; decision support systems; AI (reinforcement learning, machine learning). Motivation
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develop and maintain the software for this shared demonstrator vehicle. Job requirements Completed (or about to complete) a MSc degree related to any of: artificial intelligence, machine learning
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situated knowledge on corridor potentials for housing, to experiential forms of learning based on embodied experiments with alternative social practices. The conceptual and methodological approach is to
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- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute to a corpus of geo-analytical scenarios with
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(including ultra-high-field and ultrafast MRI) Computational and network neuroscience Machine learning and biologically inspired AI Vision science and predictive coding Clinical neuroscience and