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interventions, support policy making and optimize control strategies. Our approach is highly multidisciplinary, looking at infectious diseases through multiple perspectives, multiple scales and multiple data
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broad impact across multiple clinical and neuroscientific disciplines. A strong foundation of technical skills in artificial intelligence applications is essential for success of this project. Cutting
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generative design tools such as HEEDS, and/or the Dakota or RAVEN uncertainty quantification tools. Experience with FORTRAN, C, and/or C++ applied programming. Knowledge of Python, Java, or other scripting
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analysis of (1) decarbonization pathways for energy- and emissions-intensive industries and (2) material circularity pathways in a low-carbon future. The candidate would conduct research across multiple DOE
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syndromes, cancer, and other diseases. We leverage a close collaboration with the National Institute of Health's Perinatology Research Branch. Our research has been funded by multiple grants from NSF, NIH and