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Integrated optics is currently experiencing unprecedented growth, driven largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing
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, experience working with large-scale geospatial datasets and high-performance or cloud computing, and demonstrated expertise in advanced machine learning. Experience leading research projects, managing budgets
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SINTEF. The project aims to develop an automated high-throughput platform for physiologically relevant cell research by combining robotics, microfluidics, advanced sensors, cloud-connected software, and
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relevant cell research by combining robotics, microfluidics, advanced sensors, cloud-connected software, and artificial intelligence. The successful candidate will become part of a multidisciplinary
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atmospheric circulation, cloud formation, and heat transport in water world atmospheres. Interpret observations of water worlds by comparing atmospheric simulations with measured spectra. Assess the climatic
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slowly, or act quickly but lack robust planning. Frontier models typically depend on heavy compute, cloud inference or controlled settings, limiting real-world use under compute, latency and energy
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, cloud formation, and heat transport in water world atmospheres. Interpret observations of water worlds by comparing atmospheric simulations with measured spectra. Assess the climatic conditions and
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Python and modern machine‑learning development, including version control (Git), testing, and reproducibility; experience with cloud-based solutions (e.g., Azure) is a plus. In our international working
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largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing applications. As AI models continue to increase in size and computational complexity
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is related to clouds, radiation, and atmospheric circulation. Climate models are at the core of our research, in particular models that simulate global weather and climate at kilometer-scale resolution