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discover and screen Critical minerals and materials (CMMs) transporters. This platform will enable functional screening of large transporter libraries across multiple metals, generating sequence-to-function
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augmentation. Experience applying deep learning methods to biological sequence or other omics data. Demonstrated rigor in model evaluation and experimental design, including selection of appropriate baselines
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fathers) You will: Run and test the ELM-FATES (E3SM Land Model configured to include the Functionally Assembled Terrestrial Ecosystem Simulator) against multiple observational datasets at site
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Description Multiple postdoctoral fellowship opportunities are available with The Institute for Emerging CORE Methods in Data Science (EnCORE), a TRIPODS Phase II institute funded by the National
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Constant Interaction - Frequent 3 to 6 Hours Customer/Patient Contact - Occasional Up to 3 Hours Multiple Concurrent Tasks - Frequent 3 to 6 Hours Work Environment UC Davis is a smoke and tobacco free campus
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Strong organizational skills while working on multiple projects with frequent interruptions Preferred Qualifications: Knowledge of organization, college and departmental formal and informal policies and