USDA-ARS SCINet/AI-COE Postdoctoral Fellowship in Integrating Multiple Data Streams into Forecasts of Arthropod-Borne Livestock Disease Emergence and Spread
Requirements
- AI
- machine learning
- data science
- scientific computing
- high-performance computing (HPC) clusters
Responsibilities
- develop iterative forecasts for the spread of a viral arthropod-borne livestock disease from Mexico into the United States
- develop and apply new technologies, including artificial intelligence (AI) and machine learning, to help solve complex agricultural problems
- synthesis, integration, and analysis of large, diverse datasets that benefit from high-performance computing (HPC) clusters
- facilitate cross-disciplinary, cross-location research through collaborative research on problems of interest to each applicant and amenable to or requiring the HPC environment
- Training will be provided in data science, scientific computing, AI/machine learning, and related topics as needed for the fellow to complete their research.
Other
- A postdoctoral research opportunity
- motivated postdoctoral fellows
- research towards developing iterative forecasts
- Under the guidance of a mentor
- The participant will research
