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complex terrain regions. CMAS does this by innovating on the fronts of meteorological data acquisition, analysis, and interpretation (https://www.bnl.gov/cmas/). The CMAS work portfolio is conducted within
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and metabolic flux analysis. Knowledge and experience in Constraint-Based Modeling of metabolic networks. Experience in plant cultivation in growth chambers of green house space. Experience in the use
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for scientific and security applications; (ii) ML model optimization for inference speed and deployment for real-time analysis; and (iii) AI model training for analog in-memory computing. The position provides
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, foundation models, vision-language models, and computer vision for various problems relating to scientific discovery. Work in interdisciplinary collaborations with subject matter experts on various aspects