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Field
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, embedding pipelines, and LLM-integrated systems. Strong background in network science and graph analytics, including: Graph modeling and analysis using tools such as NetworkX Graph-based ML or graph neural
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description POSITION OVERVIEW Academy: Academy of Artificial Intelligence and Advanced Technology Position
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for the Division of Computational Science and Technology. You will contribute to research projects on structured tensor-network neural architectures, quantum-inspired machine learning, and their applications
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finite element methods (FEM) and deep learning approaches. Differentiable FEM enables direct access to sensitivity information within non-linear and coupled systems, while neural networks can be used
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. Strong background in network science and graph analytics, including: Graph modeling and analysis using tools such as NetworkX Graph-based ML or graph neural networks (GNNs) is a plus Deep understanding of
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, neural networks) to be able to analyze data sources and bias mechanisms. Knowledge of the challenges of interoperability and digital infrastructure in resource-constrained countries. Knowledge of African
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further developed using different forms of AI, both traditional AI and neural network-based methods, to improve adaptability, safety, human comfort and resilience. The research will include AI for robot
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: Development of a computer vision-based machine learning model, using Convolutional Neural Networks or similar architectures, for the early detection of diseases in pome fruit orchards. Tasks: - Review machine
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of multi-agent coordination, decentralized control, target assignment, or swarm robotics. Familiarity with graph neural networks, attention mechanisms would be advantageous. Experience with computer vision
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with traffic jams spreading like oil spills over entire networks. We believe traffic management based on reliable predictions is therefore crucial to ensure accessibility and safety, especially during