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Field
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constructed workflows. The selection of relevant geodata (maps), the construction and execution of workflows (i.e., transformations), and ensuring their semantic validity and correctness all play a crucial role
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Dipartimento di Ingegneria dell'Informazione - Università degli studi di Padova | Italy | 3 months ago
will contribute to the design and development of the Multimodal Semantic Integration Platform (WP3) within the HEREDITARY project (Horizon Europe RIA, grant 101137074). The activity addresses two
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Dipartimento di Ingegneria dell'Informazione - Università degli studi di Padova | Italy | 3 months ago
project (Horizon Europe RIA, grant 101137074), the activity targets Work Package WP2 (Clinical Use Cases and Federated Networking Infrastructure) and WP3 (Multimodal Semantic Integration Platform). The main
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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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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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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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-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