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Apply Now How to Apply Applications should be sent to [email protected] and [email protected] with the subject line: Postdoctoral Application - Granular materials using graph theory. Interested
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(m/f/d) in Graph Learning. Project overview This position offers a rare opportunity to contribute to the future of machine learning for graph-structured data. While machine learning has transformed
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To support the UrbanHeatMap project, which aims to develop scalable, high-resolution ambient temperature mapping methods by integrating outdoor microclimate measurements, mobile sensing data, satellite-derived land surface temperature, and urban morphology information. The Research Assistant...
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air temperature maps • Develop and train Graph Neural Network (GNN) and Long Short-Term Memory (LSTM) architectures to model complex spatial and temporal dependencies in urban microclimate data
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://dimag.ibs.re.kr/ Successful candidates for the research fellowship positions will be new or recent PhDs with outstanding research potential in all fields of Discrete Mathematics with emphasis on Structural Graph
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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system to track proposals. Evaluate and perform preliminary analysis of the data using graphs, charts or tables to highlight the key points of the research results collected in accordance with the research
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, such as InfiniBand and Ultra Ethernet. Our project will also deliver a comprehensive set of PyTorch libraries, encompassing various optimized models for scientific applications, including Graph Neural