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that keeps a productive lab running. Research and Scholarship: The core of this position is an independent yet lab-aligned research program centered on the neural circuit mechanisms of epilepsy, using in vivo
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related to modeling and simulation of biological systems, 3) very good IT skills, in particular the ability to program in Python, 4) very good knowledge of machine learning methods, neural networks, and
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Università degli Studi di Roma Tor Vergata - Dipartimento di Ingegneria dell'Impresa Mario Lucertini | Italy | 3 months ago
research relies on a real-world dataset covering the entire Italian Twitter sphere in 2022 and aims to evaluate modular Graph Neural Network architectures for scalable and interpretable node representation
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predict interaction effects. Unlike robot-specific neural network models, the proposed approach aims to learn a universal representation of local interactions (fluid-structure, robot-robot, robot-object
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environments, open-source genomics pipelines, and workflow management systems (e.g., Snakemake). Experience or knowledge of artificial intelligence, such as implementing neural network models, is advantageous
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or hard constraints, operational bounds (voltage limits, capacity, phase balance), and network topology through graph neural network architectures. You will build validated benchmark datasets and an
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow – Human Neuroimmunology, Brain Organoids and Multi-omics Department MS Research Network | Department of Medicine
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staff position within a Research Infrastructure? No Offer Description Activities: The scholarship recipient will be responsible for implementing and comparing quaternion-valued deep neural networks
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at the intersection of AI, deep learning, computational neuroscience, and vision science. You'll develop biologically realistic neural networks to understand how individual differences in the brain shape perception