Summary
The Neuroinformatics (NI) Core at Kansas State University, initially established with COBRE funding, is extending its capabilities in Phase 2 to include deep expertise in machine learning and artificial intelligence (ML/AI) models, providing secure and efficient access for data sharing, analytics, computational modeling, and high-performance computing (HPC) for neuroscience research.
What they want
The NI Core will extend its skills in systems, workflow design, and high-performance computing (HPC) to incorporate deep expertise in machine learning and artificial intelligence (ML/AI) models. It will provide secure, fast, and efficient access for data sharing, analytics, computational modeling, and HPC, specifically supporting the management, analysis, and modeling of large data sets from neuroscience studies (e.g., neuroimaging, neural recordings, auditory learning, transgenic Alzheimer’s Disease modeling, quantitative behavioral measurements). During Phase 2, the core will add support for on-premises and cloud-based sensitive data and analysis in partnership with the K-State Chief Information Security Officer and the Research Information Security Enclave (RISE). The core will support all three primary projects, two other research cores, and all CNAP programs, promoting extramural funding success and the graduation of junior investigators.
Deliverables
- Secure, fast, and efficient access for data sharing
- Analytics support for large neuroscience datasets
- Computational modeling capabilities
- High-performance computing (HPC) resources
- Support for machine learning and artificial intelligence (ML/AI) models
- On-premises and cloud-based sensitive data analysis support
- Training opportunities for machine learning and data analytic techniques
Technical requirements
- High-performance computing (HPC)
- Machine learning (ML) models
- Artificial intelligence (AI) models
- Microsoft Azure cloud (for RISE system)
- Compliance with appropriate standards for sponsored-research efforts
Key personnel
- Faculty advisors (two added)
- Graduate students (two added)
