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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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neural networks on synchronised video, audio, and text data to automatically detect how gestures or gaze contribute to meaning in conversations.- Bridging cognitive science and AI to model how humans
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Neural mechanisms underlying accent processing in naturalistic conversations: Insights from brain oscillations and functional neuroimaging Prof. Guillaume Thierry Applications are invited for a
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-funded project Print4Life, a Marie Sklodowska-Curie (MSCA) doctoral network led by Prof. Cecilia Persson, Uppsala University. Print4Life – Advanced Research Training for Additive Manufacturing
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 19 days ago
processing and will involve EEG and MRI experiments as well as realistic modeling of biological neural networks. It is a cooperation between the TU Berlin, the TU Chemnitz, the Czech Academy of Sciences, and
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./week) TV-L E 13for the DFG Project " The neural dynamics of causal evidence accumulation in multisenso-ry perception" as of 1.1.2026 or as soon as possible, limited for 3 years. The project investigates
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
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. Advanced modeling techniques, such as surrogate modeling, machine learning, and physics-informed neural networks, will be applied to accelerate simulations and enable real-time performance. A strong emphasis
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efficient, adaptive use of multistable networks, offering an alternative to energy-intensive digital systems with rigid bits and separated memory and computation. In this project, we aim to design and realize
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engineering, computational neuroscience, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from