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  • SCINet Home | SCINet | USDA Scientific Computing Initiative
    SCINet is a USDA-ARS initiative providing high-performance computing, data transfer and storage, and computing support and training for agricultural research
  • Storage Locations | SCINet | USDA Scientific Computing Initiative
    This guide provides detailed information about the storage locations provided by SCINet and how to use them Figure 1 below illustrates how these storage locations are related To learn more about how to transfer files among them, please see the File Transfer Methods guide Figure 1 Recommended procedures for managing data on SCINet infrastructure Move data to Juno Copy data to target HPC
  • SCINet Ceres | SCINet | USDA Scientific Computing Initiative
    home and project directories data transfer to from SCINet clusters basic SLURM job scheduler commands computing in interactive mode with salloc accessing Ceres software modules computing in batch mode with a batch script Technical Overview Ceres is the dedicated high performance computing (HPC) infrastructure for ARS researchers on ARS SCINet
  • ARS AI Innovation Fund (FY26) | SCINet - USDA
    Overview The goal of the ARS Artificial Intelligence Center of Excellence (AI-COE) is to enable innovative ARS science by promoting the adoption and use of AI and machine learning (ML) tools and methods in agricultural research For FY26, the AI-COE expects to fund 4 to 6 proposals at up to $100,000 each for activities to encourage and promote AI-related research in agriculture For examples
  • Overview of SCINet Training Resources - USDA
    Overview of SCINet Training Resources One of SCINet’s main objectives is training scientists in computational methods to empower agricultural research We are doing this in several ways We offer online and in person trainings, support topic-specific working groups, and provide help, training, and tutorials for scientists
  • Large Language Model Support | SCINet | USDA Scientific Computing . . .
    Generative large language models (LLMs) can accelerate and augment multiple facets of agricultural research across a wide range of scientific disciplines USDA policy allows for the use of generative AI (including LLMs) for scientific research, and, since SCINet is intended exclusively for scientific research, the use of locally hosted LLMs is allowed on SCINet SCINet is an excellent
  • ARS AI Center of Excellence and SCINet Graduate Student Internships . . .
    Overview The ARS Artificial Intelligence Center of Excellence (AI-COE) and SCINet are seeking ARS scientists who wish to serve as graduate student internship mentors in the spring or summer of 2026 We want each of our interns to have an outstanding experience, which means we need outstanding ARS mentors and research projects!
  • USDA - CroplandCROS
    Cropland Collaborative Research Outcomes System (CROS) Explore, analyze, and download U S agricultural commodities from the Cropland Data Layer (CDL)
  • Open OnDemand Interface | SCINet | USDA Scientific Computing Initiative
    Open OnDemand is an intuitive, innovative, and interactive interface to remote computing resources The key benefit for SCINet users is that they can use any web browser, including browsers on a mobile phone, to access Ceres There are several interactive apps that can be run in Open OnDemand including Jupyter, RStudio Server, Geneious, CLC Genomics Workbench, and more The desktop app allows





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