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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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This position is in person at J.J. Pickle Research Campus in North Austin. Purpose To use advanced geochemical modelling to devise attribution monitoring methods for CO2 leakage in groundwater and surface
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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