About

• Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world's best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer. Development and Implementation: Design LLM-based agent systems for system areas. Implement prototypes and conduct experiments to test and validate them. Research and Analysis: Conduct thorough research on emerging trends in agent systems for academic research and scientific discovery. Collaboration: Work closely with cross-functional teams, including hardware engineers, software developers, and data scientists, to integrate your ideas with existing and future agent projects. Documentation and Reporting: Prepare detailed documentation of simulations, methodologies, and findings. Present results and insights into team members and stakeholders. Innovation and Problem-Solving: Identify challenges and bottlenecks in agent systems and propose innovative solutions. Currently enrolled in a bachelor's, master's, or PhD program in Computer Science, Electrical Engineering, Machine Learning, Mathematics, or a related field. Proficient in programming languages such as C/C++ or Python. Familiar with fundamental concepts related to LLM, prompt engineering, and LLM-based agents. Experience in AI for systems and/or systems for AI. Passionate about addressing real-world large-scale research problems using AI models. Experience with LLM or one specific system direction would be a plus. Proficient analytical and problem-solving skills and communication skills, both written and verbal.