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humans in playing board and computer games, driving cars, recognizing images, reading and comprehension. It is probably fair to say that an artificial neural network can perform better than a human in any
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or equivalent Skills/Qualifications - PhD in bioinformatics or related subjects - Expertise in python coding - Experience and good understanding of neural networks and machine learning - Fluent written and spoken
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of the project is to design, model and simulate neural networks based on magnetic skyrmion nucleation and propagation. The second objective is to fabricate these hardware neural networks, characterize
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. The project focuses on high-precision optical computing for neural network applications and leverages a radically new digitized optical computing architecture. You will play a central role in advancing
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research fellow to work on the development of Physics-informed neural networks (PINNs
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
complexes. The successful candidate will develop novel graph neural network (GNN) architectures to learn dynamic information from molecular dynamics (MD) simulations of protein-protein and protein-nucleic
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. The position is part of the research project "Neural networks for homomorphic encryption", funded by Inria. Fully homomorphic encryption (FHE) enables computations to be performed directly on encrypted data
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desirable. Familiarity with explainable AI, causal inference, or biologically inspired neural networks, as well as experience collaborating with experimental laboratories, will be considered strong assets
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communications Computing & Networking: QuMIMO, Quantum Error Correction, Multi-partite systems, Q Network Coding, HQCNN - Hybrid Quantum-Classical Neural Networks Security & Logic: QRL - Quantum Reinforcement
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Neural Networks (SNNs); (c) have strong proficiency in PyTorch programming and model development; and (d) possess a basic understanding of brain-inspired learning methods and Large Language Models