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Field
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large-scale spiking neural networks. In close collaboration with our Mod4Comp partners (DFG Forschergruppe FOR 5880), you will develop models of performance and energy to guide the co-design of software
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communications Quantum communications Computing & Networking: QuMIMO, Quantum Error Correction, Multi-partite systems, Q Network Coding, HQCNN - Hybrid Quantum-Classical Neural Networks Security & Logic: QRL
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applied methodologies in Data and Image Analysis, Computational Imaging, Statistical Learning, Uncertainty Quantification, Robust Estimation, and Deep Neural Networks. The group combines expertise in
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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware
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aspects of machine learning focusing on efficiency, generalization, and sparse neural networks. Currently we are expanding our expertise by applying our theoretical findings also to robotics. Hybrid is our
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multiple brain areas in an optimised way. This may include neural network and neural mass modelling of large-scale brain activity during and after stimulation, and experimental tACS in healthy participants
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AI researchers from ANITI, IMT and CERFACS, as well as with researchers/engineers in weather forecastings from the CNRM (Météo-France). Hybridization methods between neural networks and physical models
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sciences or a related field, with practical experience in molecular and cellular techniques, preferably including work with iPSCs and iPSC-derived neural or myogenic cell types. You have a strong passion for
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. Develop the Core AI Predictor - You will explore and train advanced models, such as Graph Neural Networks (GNNs), to solve the key challenge: distinguishing benign aging from true failure precursors
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, physics or a similar area - very good programming skills in Python - good prior experience with neural networks using common Python-ML libraries such as PyTorch - background knowledge in computational