Machine Learning and Unconventional Computing Paradigms ASPIRE Graduate Intern
Savannah River National LaboratoryAbout the role
Internship research opportunity (Summer 2026) for graduate students with interests in hardware-software co-design of Machine Learning (ML) algorithms and Beyond-CMOS unconventional computing paradigms. The intern will contribute to an ongoing project focused on developing and implementing ML solutions for emerging computing platforms for sensing and monitoring applications.
The intern will contribute to the hardware-software co-design of ML algorithms for unconventional computing paradigms by implementing and optimizing ML models under some hardware constraints.
Minimum Qualifications
Must be a U.S. Citizen.
Currently enrolled in a graduate program or higher in Computer Engineering, Computer Science, or other related disciplines.
Must have a minimum GPA of 3.4 or higher and submit a transcript prior to hiring
Preferred Qualifications
Strong Python programming skills
Knowledge and experience in Machine Learning (ML)
Experience with ML frameworks
Experience in electronic circuit design
Excellent written and communication skills
Experience with using the command line (bash)
Experience in or knowledge of optimization techniques and approaches
Apply for this role
Generate a tailored application kit with a matched cover letter, interview prep, and CV highlights — in under 60 seconds.
Apply Now →Generate Application KitFree account required — sign up in 30s