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semantic representations. Develop methods to assess AI-generated hypotheses for plausibility, novelty, evidence support, contradiction, uncertainty and explainability. Publish in leading NLP, AI and
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Recommendation Service, which leverages Enterprise Architecture models (e.g., ArchiMate and EIRA) to derive semantic requirements from stakeholders’ goals, requirements, business objects, and integration patterns
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
photorealistic but also exhibit high semantic fidelity, temporal coherence, and practical usability in creative and industrial applications. 2. Main Tasks The Postdoctoral Research Fellow will be responsible
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) at LISN (Semantics and Information Extraction group) in Orsay. B. Cecconi will contribute disciplinary expertise in heliophysics and manages a dedicated data repository for radio astronomical observations
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365, or Microsoft Entra ID. Experience with Power BI, semantic models, or operational dashboards. Experience combining data from multiple systems. Familiarity with TeamDynamix. Experience using Git
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here: https://itacademy.harvard.edu/ . Job Description Harvard Library and Harvard University IT are advancing the Reimagining Discovery initiative to transform how researchers, students, and the global
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validation, semantic curation, data architecture, and data transformation and translation. The incumbent may also contribute to strategic initiatives and business development efforts by evaluating and
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-based AI for multidisciplinary tumor boards. The successful candidate will develop LLM-based pipelines, semantic harmonization, and transformer-based temporal models on a large multimodal oncology dataset
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concepts (e.g. agents, semantic views, semantic search) Foundational knowledge of dbt for data transformation and analytics engineering Experience with Git and version-controlled workflows Please Note
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the consistency, interoperability, and analytical potential of the dataset. The main task consists of TEI/XML encoding and refinement of textual materials, aiming to enhance both the structural and semantic