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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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. Travis Mallard (Massachusetts General Hospital & Harvard Medical School). Both are interdisciplinary projects integrating theory and methods from developmental psychology and quantitative genomics
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of sedimentology, geochemistry, and microbiology, and general use of destructive, extraction-based methods that are designed for the analysis of large sediment samples. These bulk methods are quantitative but
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Postdoctoral Fellow position focused on developing advanced, AI-enabled methods for clinical decision support in precision oncology. The fellow will work at the intersection of computational innovation
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. Required Qualifications · PhD in Geophysics · Experience with land seismic acquisition, DAS, and time-lapse monitoring · Proficient in computer programming · Extensive publication and presentation record
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collection, including cognitive assessments such as computer-based testing, questionnaires, and health measurements, as well as brain measures such as electroencephalography and near-infrared spectroscopy
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thinking skills, and ability to work as part of a multidisciplinary team. High computer proficiency, including basic MS Office, MS Access, graphics, and database software. Basic project management and