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the safe deployment of AI systems in real-world environments. Current research activities focus on topics such as: Constrained Generative models for graph and tabular data. Security, robustness, and
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entities, events, relations, causal claims and mechanistic pathways from scientific literature. Build pipelines that link textual evidence to biomedical ontologies, knowledge graphs, causal models and
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equivalencies: https://hr.uky.edu/employment/working-uk/equivalencies Required Related Experience 3 yrs Required License/Registration/Certification None Physical Requirements Sitting for long periods of time with
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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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-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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Qualifications: Advanced skills in Microsoft Excel (creating/using formulas, tables, charts and graphs), Word (mail merge), Outlook (complex calendaring), One Drive, SharePoint and Adobe Acrobat Professional
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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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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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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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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