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groups, photovoice). Skilled in qualitative data analysis and community-based approaches. Demonstrated commitment and ability to collaborate across disciplines to address complex challenges. Strong
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convolutional neural networks (CNNs), generative AI methods such as diffusion models, and interpretability techniques commonly applied in hydrology including SHAP or LIME for explaining outputs of forecasting
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teaching, presenting work at national and international meetings, and working with care providers and health care delivery networks to implement research in practice. Live in Austin a Vibrant, Lively
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skills. Preferred Qualifications Experience convening and leading a complex, multi-faceted research effort with multiple stakeholders. Experience with public presentations in a non-academic environment