USDA ARS Postdoctoral Fellowship Program in Big Data Science and AI Research
Multiple 2-year MS and postdoctoral research opportunities are currently available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS) located at one of the regional ARS locations or with one of our collaborating universities. 100% telework options are possible depending on the position. The SCINet/Big Data Program in collaboration with the AI Center of Excellence at ARS offers exciting research opportunities to motivated participants interested in solving agricultural- or natural resource-related problems at a range of spatial and temporal scales, from the genome to the continent, and sub-daily to evolutionary time scales. One of the goals of these programs is to develop and apply new and emerging technologies, including artificial intelligence (AI) and machine learning, to help solve complex agricultural problems that depend on collaboration across scientific disciplines and geographic locations. Many of these questions rely on the synthesis, integration, and analysis of large, diverse datasets that benefit from high performance computers (HPC) or a cloud computing environment. These opportunities are designed to facilitate cross-disciplinary, cross-location research through collaboration on problems of high priority to the USDA ARS and require an HPC or cloud computing environment. Training will be provided in specific AI, machine learning, deep learning, data science, and/or statistical software as needed for the success of the position.
This unique fellowship program is multi-faceted. All participants will spend time at ARS headquarters in Beltsville, MD for some of their training, but will be based at ARS regional laboratories for mentoring in individual research projects by ARS scientists or university faculty, primarily at Mississippi State University or Iowa State University. Each participant will also be expected to participate in collaborative research with scientists at other ARS units or universities, and in program-level activities in support of Big Data and high performance computing.
Interested applicants are encouraged to visit the specific ORISE link (below) for more information about a specific position and to apply.
About the USDA ARS: The ARS mission involves problem-solving research in the widely diverse food and agricultural areas encompassing plant production and protection; animal production and protection; natural resources and sustainable agricultural systems; and nutrition; food safety and quality. The programs are conducted in 46 of the 50 States, Puerto Rico, and the U.S. Virgin Islands. Programs are also carried out in cooperation with several foreign countries. For ARS to maintain its standing as a premier scientific organization, major investments in computing, networking, and storage infrastructure are required as well as trained scientific personnel. Training in data and information management are integral to the integrity, security, and accessibility of research findings, results, and outcomes within the ARS research enterprise. USDA ARS Chief Science Information Officer, Dr. Debra Peters (ARS-CSIO at usda dot gov) can be contacted for additional information.
Specific postdoc opportunities for 2021-2022 include the following:
Machine learning and AI in Human Nutrition: learn about challenges in predicting effects of diet on health outcomes while learning a range of computational skills needed to conduct these analyses (ARS location: Davis, CA). https://www.zintellect.com/Opportunity/Details/USDA-ARS-2021-0008
Integrating Breeding Platforms and Bioinformatic Analyses: develop and implement software pipelines to integrate analysis of phenotypic and genomic resources being collected by specialty crops breeding programs to establish technology driven breeding programs (ARS location: Raleigh, NC). https://www.zintellect.com/Opportunity/Details/USDA-ARS-2021-0001
Computational tools and pipeline development for metagenomic data analysis training fellowship: gain experience with development of software pipelines for metagenome analysis, implement pipelines on high-performance computing (HPC) clusters, and refine pipelines to work for different data sets (ARS location: Maricopa, AZ). https://www.zintellect.com/Opportunity/Details/USDA-ARS-2021-0003
Small unmanned aerial systems (sUAS) remote sensing of agro-ecosystems and high-performance computing: learn about the challenges of sUAS data, including issues related to collection, processing, and use while learning a range of computational skills needed to conduct complex analyses of drone data, including machine learning approaches to image classification (ARS location: Tifton, GA). https://www.zintellect.com/Opportunity/Details/USDA-ARS-2021-0007
Higher Level Analytics in a Complex Systems Approach to Reduce Risk of Salmonella: learn about the challenges in producing a safe meat supply while learning a range of computational skills, including machine learning, including predictive analytics, AI and machine learning technologies, needed for control of Salmonella in food production systems (ARS location: Clay Center, NE). https://www.zintellect.com/Opportunity/Details/USDA-ARS-2021-0059
Training in the Coordination of Big Data Science Programs: learn about the challenges associated with managing, coordinating, and training a diverse scientific workforce to access and successfully use high performance computing resources for agricultural research (ARS location: Beltsville, MD). https://www.zintellect.com/Opportunity/Details/USDA-ARS-2021-0002
High Performance Computing and AI Technologies in Agriculture: learn a range of AI computational skills on high performance computers (HPCs) while predicting dynamics of agro-ecosystems (ARS location: Starkville, MS). https://www.zintellect.com/Opportunity/Details/USDA-ARS-2021-0035
High Performance Computing and Prediction of Geospatial Dynamics: learn about the challenges in predicting dynamics of complex agro-ecosystems while learning a range of computational skills needed to conduct complex geospatial analyses in an HPC environment (multiple ARS locations). https://www.zintellect.com/Opportunity/Details/USDA-ARS-2021-0005
Development of novel algorithms and machine learning models for integrated analysis of agricultural systems: develop new analysis methods for georeferenced agricultural data with emphasis on epidemiology and disease ecology. For more information, please contact Dr. Ram Ramkumar (ramkumar at cse dot msstate dot edu).
Modeling complex dynamic systems related to animal production and health: develop mathematical and stochastic models of complex dynamics systems related to animal production and health. Methods may include system dynamic stock and flow modeling or other programing methods. For more information, please contact Dr. David R. Smith (dsmith at cvm dot msstate dot edu)
Biomathematician/Biostatistician to develop novel mathematical and statistical tools for describing spatial phenomena using high-resolution remote sensing and biotelemetry datasets, coupled to applications in high-performance computing to facilitate rapid data analysis. https://explore.msujobs.msstate.edu/en-us/job/500405/postdoctoral-associate
Geospatial Statistician/Spatial Data Scientist: apply your spatial statistics skills to diverse datasets ranging from epidemiology in domestic livestock to contact tracing in wild carnivores. https://explore.msujobs.msstate.edu/en-us/job/500273/postdoctoral-associate
Specific MS opportunities for 2021-2022 include the following:
Research Opportunities in High Performance Computing (Artificial Intelligence) to develop and apply new technologies, including artificial intelligence (AI) and machine learning, to help solve complex agricultural problems that also depend on collaboration across scientific disciplines and geographic locations (ARS location: Beltsville, MD). (Contact Jennifer Woodward-Greene with questions and to apply; jennifer dot woodward at usda dot gov)
High Performance Computing and Prediction of Geospatial Dynamics: learn about the challenges in predicting dynamics of complex agro-ecosystems while learning a range of computational skills needed to conduct complex geospatial analyses in an HPC environment (multiple ARS locations). (Contact Debra Peters with questions and to apply; deb dot peters at usda dot gov)
Bioinformatic Analyses and Training Fellowship: learn a diverse array of bioinformatic analyses on the HPC, including high throughput sequencing technology for organisms of significant economic importance in agriculture, and for the pests that hinder the full potential of crops, livestock, and aquaculture (ARS location: Ames, IA or other locations). (Contact Brian Scheffler with questions and to apply; brian dot scheffler at usda dot gov)