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science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood biomarkers, and
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Qualifications: Ph.D. in applied hydrology, civil engineering, computer science, geoscience, or related field. Skills and Knowledge: Strong interest in (or skilled in) the development and application of hydrologic
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machine learning libraries such as PyTorch. Experience with version control systems (e.g., Git) and collaborative software development. Background Investigation Statement: Prior to hiring, the final
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