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Field
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, Skills, and Abilities: Expert in data analysis, modeling, machine learning, and AI, using Python and SQL, with extensive experience in libraries and frameworks such as Pandas, NumPy, scikit-learn, Gensim
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maintain collaborative partnerships with faculty and staff across the institution, demonstrated through prior experience or a strong capacity and willingness to learn. Experience in and/or demonstrated
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linguistics, semantics, syntax, pragmatics, computational linguistics, phonology, or sociolinguistics. We would like to see candidates who can communicate with and learn from both linguists and scholars in
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Center for Biologics Evaluation and Research (CBER) | Southern Md Facility, Maryland | United States | about 2 hours ago
are held in zoos, research facilities, venom producing facilities, and by private individuals. Exotic antivenoms are also acquired by US military for treatment of personnel positioned in other nations
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learn best practices in instructional design and health communication, including web communication, application of CDC’s quality training standards, user experience, digital content design, and plain
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crop area and learn basic agronomic, data collection, and plant breeding methodologies in trials and nurseries planted at the USDA-ARS. Learning Objectives: The project assignments will provide you with
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, chromatin profiling, genomics, spatial transcriptomics and single-cell data. Apply statistical, machine learning, and network-based approaches to analyze high-dimensional biological data. Collaborate closely
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 2 hours ago
artificial intelligence (AI) and statistical programming skills in R and/or SAS by implementing end-to-end machine learning pipelines, including data preprocessing, model training, cross-validation, simulation
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where new health hazards (such as vapor intrusion or changes in chemical toxicity) have emerged. Learning Objectives: You will have the opportunity to: Learn ATSDR’s approach to conducting public health
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by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain