Smart Data Management for Scientific Discovery
Join cutting-edge research designing intelligent systems that accelerate scientific breakthroughs through smarter data management
The Challenge
Modern scientific research generates massive amounts of data from simulations and observations, but analyzing all this data to find meaningful patterns is extremely expensive and time-consuming. Scientists need better ways to quickly identify important features without having to process everything.
Our Solution
You’ll help design and build an innovative metadata management system that uses machine learning to intelligently organize, place, and query scientific data. This system will dramatically reduce “time-to-insight” – helping scientists make discoveries faster than ever before.
What You’ll Do
- Research and develop scalable data management algorithms
- Build software tools used by scientists worldwide
- Apply machine learning to real-world scientific problems
- Collaborate with leading researchers in high-performance computing
About SCS Lab
The Scalable Computing Software Lab has over 20 years of research excellence in high-performance computing. With hundreds of publications, thousands of citations, dozens of patents, and more than 20 active researchers, SCS Lab creates technology that powers scientific discovery globally.
Opportunity Details
- Faculty Mentor: Professor Anthony Kougkas
- Department: College of Computing – Computer Science
- Eligibility: 3rd & 4th year undergraduates, current and newly admitted graduate students
- Best Fit Majors: Computer Science, Computer Engineering, Software Engineering
- Application: Ongoing – apply anytime
Research Assistantship Available
Up to $5,000 per semester based on performance and funding availability
Ready to accelerate scientific discovery through intelligent data systems?
Contact: scslab@iit.edu or akougkas@iit.edu
