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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a
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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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topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and iterative solvers. Successful applications will work
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of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a
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working in radiological environment. Experience in heat transfer and thermal modeling/simulation using finite-element analysis (FEA) or other software. Ability to work within a multi-disciplinary team