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management, with experience in statistical analysis and process-based modelling. A person with training in database development and management, as well as experience and interest in modeling soil carbon
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; preparing biological samples for testing; coordinating and optimizing insect behavioral assays Data Management: maintaining meticulous experimental data records, digital database entry, and basic statistical
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, transgenic/gene-targeted mouse models, and natural hosts (e.g., cattle, deer, and sheep). Note: Research will be carried out in BSL-2+ or BSL-3 laboratories. The fellowship activities involve utilizing
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in the one of the relevant fields. Preferred Skills: Strong skills in data analysis and database management; statistics and programming knowledge preferred (e.g. R/R Studio, SAS, Stata, SQL, Python
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of large population-based and healthcare databases within Division of Diabetes Translation's Surveillance, Epidemiology, Economics and Statistics Branch (SEESB). Under the guidance of experienced CDC
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strategies, inclusion/exclusion criteria, and analytical plans. Designing and executing robust search strategies across multiple scientific databases (e.g., PubMed, Embase, Cochrane Library). Conducting title
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state-of-the-art experimental and computational models for solving water resource problems worldwide. CHL research and development addresses water resource and navigation challenges in a variety of
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application of foundation models for fungal DNA and protein sequences. With ARS and external AI knowledge-holders, you will adapt long-context DNA language models to fungal genomes. These DNA-language models
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expensive and dangerous health threats, and responds when these arise. Research Project: You will gain training and experience in the analysis of large population-based and healthcare databases within
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. During this training opportunity, you will have the opportunity to be involved in the development of a training model to predict PRRSV disease outcomes in field-collected samples from pigs infected with