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Field
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) equipped with a cryogenic stage for surface analysis - Develop computer code (e.g. Python) for the development and analysis of optical cavities Qualifications § PhD degree in Materials, Electrical
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to root patterning. Integrate molecular and imaging data into a spatio-temporal developmental framework. Research environment and approaches The project is highly interdisciplinary. The successful candidate
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 6 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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. Experience working with medical images. Very good computer programming skills and physics background is essential. Desired Qualifications* Nuclear medicine imaging/dosimetry experience. Experience in image
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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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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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size exclusion chromatography) Conduct protein binding experiments (ELISA or SPR) Develop and optimize protocols for sample preparation and imaging by cryo-EM Collect and analyze cryo-EM data using a
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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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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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of maintenance. The project aims to develop an integrated decision-support framework that combines inspection images, sensor data, and engineering interpretation to enable more transparent, evidence-based