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basic technologies, computer vision, image understanding, and other multi-media sensing and recognition techniques are widely studied. In addition, machine learning including deep neural networks
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have become a major challenge for understanding, recording, and modulating neuronal network activity, ranging from in vitro cellular models to implantable neurotechnological applications. In the long
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Conference on Neural Networks (IJCNN), pages 1–10, July 2022. doi: 10.1109/IJCNN55064. 2022.9892277. URL https://ieeexplore.ieee.org/document/9892277/?arnumber= 9892277. G. Bellec, D. Salaj, A. Subramoney, R
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and processing of multi-omics biomedical data from various public sources. 2. Development and training of AI models based on Graph Neural Networks (GNN) and Kolmogorov-Arnold Graph Neural Networks
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Training and deployment of Spiking Neural Networks And will allow you to develop competences in Tactile Perception Spiking Neural Networks ESSENTIAL REQUIREMENTS To be registered as a student in an
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molecular and cellular processes and neural networks to complex patterns of perception, action and memory in humans and animals. In line with Leibniz’ maxim “Theoria cum Praxi” LIN is committed to fundamental
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project), create a unique opportunity to apply machine learning and neural network methodologies, in conjunction with simplified ice sheet models, to advance understanding of ice sheet basal processes and
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approaches such as physics-informed machine learning (PINNs), graph neural networks for lattice structures, and neural operators for fast surrogate modeling, as well as AI-driven inverse design and generative
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strongly preferred. Strong Python skills, and proficiency in PyTorch and/or JAX. Ability to reason about neural network behavior from first principles: how architectural choices, regularization, and training
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, and proficiency in PyTorch and/or JAX. Ability to reason about neural network behavior from first principles: how architectural choices, regularization, and training procedures affect model behavior