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: Conduct a parametric exploration of global-scale surface process models to identify the major parameters for refuge zone formation. ➢Mission 3: Compare the models with observations, particularly those from
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foundation models and agentic AI models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization. Experience in multi
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under industrial process conditions. The group is embedded in the PROSYS research center, part of DTU Chemical Engineering. Key to this scale-down approach is to ensure measurements are made at a small
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Epic optimization or consolidation, large-scale IT integrations, and multi-entity organizational alignment Demonstrated results in digital transformation, including data analytics, clinical workflow
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programme Reference Number AE2025-0593 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0593
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programme Reference Number AE2025-0597 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0597
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Programme? Not funded by a EU programme Reference Number AE2025-0595 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https
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programme Reference Number AE2025-0594 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0594
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Framework Programme? Not funded by a EU programme Reference Number AE2025-0599 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https
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Programme? Not funded by a EU programme Reference Number AE2025-0601 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https