Summer Research Assistant - School of Computer Science - S3D

Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the curious to deliver work that matters, your journey starts here!

The Software and Societal Systems (S3D) department within the School of Computer Science explores the vital intersection of the confluence of software, systems, and society to understand how computational technologies might better serve humanity. We are studying the bigger picture of computing in context in order to develop tools, policies, methods, and much more — all in the name of making the world a safer, more equitable, better place to call home.

S3D is seeking a Summer Research Assistant to contribute to interdisciplinary research on the impact of artificial intelligence on scientific innovation, with a focus on understanding how AI reshapes knowledge production, collaboration, and discovery processes through large-scale data analysis and computational methods.

Core Responsibilities

• Support research on the impact of AI on scientific innovation
• Analyze large-scale datasets (e.g., publications, software, and scientific artifacts)
• Develop and apply data analysis workflows in Python
• Conduct citation analysis of innovation and collaboration patterns
• Assist with machine learning and/or LLM-based analysis
• Participate in mentoring junior researchers in large-scale data analysis and publication

Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University.  We are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.

Qualifications:

• Bachelor’s degree in computer science or relevant field required. Master’s degree preferred.
• Strong Python/data analysis skills
• Experience with large-scale data and computational research, especially in citation network analysis
• Familiarity with machine learning models and large language models
• Successful research publication and mentoring experience
• A combination of education and proven experience from which comparable knowledge is demonstrated may be considered.

Requirements:

• Successful completion of a pre-employment background check

Joining the CMU team opens the door to an array of exceptional benefits.

Benefits eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits, take well-deserved breaks with ample paid time off and observed holidays, and rest easy with life and accidental death and disability insurance. 

Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team to help navigate childcare needs, fitness center access, and much more!

For a comprehensive overview of the benefits available, explore our Benefits page.

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it’s about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in an exciting opportunity with an exceptional organization?! Apply today!

Location

Pittsburgh, PA

Job Function

Researchers

Position Type

Staff – Fixed Term (Fixed Term)

Full Time/Part time

Full time

Pay Basis

Hourly

More Information: