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on developing robotics and cyber physical systems solutions using machine learning and artificial intelligence to support different aspects of marine science, with opportunities to expand to other areas
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single-cell and single-nucleus multi-omics, machine learning/AI, computational biology, and experimental validation to understand cardiovascular disease progression and identify novel therapeutic targets
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Center for Drug Evaluation and Research (CDER) | Southern Md Facility, Maryland | United States | about 15 hours ago
from clinical studies. Learning Objectives: Through this opportunity you will; Establish collaboration framework with FDA internal and external stakeholders for various specific domains including opioids
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 15 hours ago
therapeutics and generic drugs. This effort covers more than just medicines. Research Project: Under the guidance of a mentor, you will engage in a hands-on learning experience involving Cell-free protein
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-guided learning activities may draw upon biomonitoring projects associated with CDC’s National Health and Nutrition Examination Survey (NHANES) and similar epidemiological studies of the U.S. population
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funds can be used effectively and on time. Research Project: This fellowship will provide an opportunity to learn alongside the Crisis Cooperative Agreement and Innovation (CCI) Team. The CCI Team manages
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history that has taken place largely in Pakistan, and plan to return to Pakistan upon completion of the fellowship. The fellow may be invited to teach a Harvard class during the course of their appointment
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, performing standardized analyses or running laboratory equipment to analyze chemical constituents of soil, plant and water samples. Learning objectives: During this opportunity, under the guidance of a mentor
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 15 hours ago
of verbatim data. As an Oak Ridge Institute for Science and Education (ORISE) participant, you will join and learn from a community of scientists and researchers engaged in an effort to use natural
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learning, and computational biology to adapt and augment existing open models for predictive biology. Approaches may include fine-tuning, parameter-efficient tuning, probing, and retrieval- or knowledge