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-scale, shallow, planar cracks in rocks, faults span a broad range of length scales (10-6-103 km) and surface-to-depth widths (1-102 km) and have a complex 3D architecture (e.g., Giampietro et al., 2025
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how DNA LLM work, and develop solutions to integrate them into the neural network architectures developed by the lab. - Focus on developing new solutions for the scalability of neural networks and large
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 11 days ago
to reconstruct open rose flowers in 3D. The key idea is to learn two neural networks that operate on different scales. The first network operates on the scale of the full flower to identify the flower architecture
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. The work will be primarily computational, focusing on the development of deep neural network model architectures and their training. It will involve extending the preliminary results we have already obtained
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in spintronics, nanomagnetism and magnetic sensing. • Contribute to the design, fabrication and characterisation of innovative devices based on magnetic thin-film architectures and spin-electronic
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neuromorphic and energy-efficient hardware architectures. Early concepts – such as Intel's MESO logic gate – illustrate the transformative potential of multiferroic technologies and motivate deeper scientific
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communication signals on our mental processes. What you will do Build novel deep learning architectures for auditory prediction (speech and/or music) prioritizing explainability and cognitive hierarchies Quantify
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. This will require adapting the architecture of the RL-EDA neural network that generates solutions, as well as adapting the reinforcement learning process to handle this heterogeneous data. Once developed
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. Measuring and predicting the effect of copy number variants on general intelligence in community-based samples. JAMA Psychiatry 2018 75(5):447-457. –Bourgeron T. From the genetic architecture to synaptic
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that methodological advances are developed with direct translational and scalability considerations. Responsabilities: Lead the development of hybrid foundation model-graph neural network architectures for gene