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minor graphing, and statistical methods. Ability to communicate efficiently and effectively with other lab personnel, students and investigators. Ability to analyze & interpret data. Preferred Education
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. Demonstrate the ability to use or learn to use graphing and scientific calculators. Ability to keep computing skills current, particularly the most commonly used software on the network. Bachelor's degree
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-agent systems b. Mapping and Scene Representations - Dynamic Scene Graphs modelling uncertainty - Unified situational awareness for multi-robot systems in large and degraded environments Qualifications
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the images and extracted text, to generate and align with existing collection metadata Align entities with existing entities/records, including the objects themselves to bootstrap knowledge graph creation
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applied to cultural heritage. Where to apply Website http://www.ispc.cnr.it Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Italy Eligibility
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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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, 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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work, studying in disciplines ranging from atomic physics and graph theory to medieval literature and blind rehabilitation. Of 101 graduate offerings available, 30 lead to a doctoral degree. Connections
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relevant to biomedical data: named entity recognition, natural language inference, or knowledge graph construction. Knowledge of graph data structures and graph platforms (Neo4j, Amazon Neptune
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programming, microfluidics, and engineering to design sophisticated algorithms for exploring and manipulating information encoded in DNA-based graphs. The position is fully funded by a prestigious CNRS