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on defined domains; Fast and scalable algorithms to fit the proposed models to data, with a theory that explains the convergence and success of these techniques; Detailed re-analysis of the performance
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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photosynthesis to join the new pilot study of Generative Pretrained Transformer for genomic photosynthesis (GPTgp). The GPTgp project aims to develop a foundational holistic model of photosynthesis that will scale
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