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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 16 days ago
models (LLMs) to enhance case definition processes by developing a prototype that demonstrates the capability of LLMs to accurately categorize and classify case definitions. The selected fellow will
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. This fellowship offers a unique opportunity to be at the forefront of groundwater technology, gaining experience on projects ranging from groundwater sampling and geophysical imaging in the field, analysis
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, operation of the scanner, data acquisition and analysis, image evaluation, and statistical analysis. The fellow will also be expected to prepare manuscripts and conference abstracts related to projects and
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imaging, lipid biochemistry, structural biology, and model systems (neurons, blood cells, immune cells, trophoblasts, and more) to uncover membrane mechanisms and develop new therapeutic strategies. Minimum
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and want to ensure that everyone can apply and be part of our recruitment processes and so we'll make reasonable adjustments if you need them - just let us know when you apply. If you need assistance
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mechanisms. Performing experiments using mouse models. Applying molecular, cellular, and immunological techniques, including flow cytometry, imaging, and genomic approaches (e.g., single-cell RNA-seq
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T-BIOM Preferably publications related real/AI generated image classification, biometrics or video processing Strong software implementation skills. Preferably 4 years+ research experience, including
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environment in which people treat each other with respect and dignity, regardless of roles, responsibilities or differences. Providing support, direction and resources enabling us to accomplish the
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and skill in programming with MATLAB or Python. Research experience in MEG, in vivo electrophysiology, in vivo two-photon/miniscope imaging, slice electrophysiology, and mouse brain surgery is desired
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on challenges related to computer vision for geophysical image data. You will investigate and develop robust methods for training models, exploring/developing approaches for multimodal data, utilize context