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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable programming applications (e.g., experimental design, machine learning for science). We do so by
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of the future, striving to improve healthcare and society as a whole. Where to apply Website https://www.academictransfer.com/en/jobs/356668/phd-in-machine-learning-for-dru… Requirements Specific Requirements
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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disconnectivity in brain networks relates to symptom networks and recovery trajectories in psychiatric patients. Apply and further develop methods from network science, machine learning, and computational
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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and
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candidate in the exciting area of multiscale and multiphysics modelling of sustainable fibrous composites, with additional focus on uncertainty quantification and machine learning. Information The context
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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 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