Opportunities in United States

Full Job Description

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. Currently enrolled in a Doctorate Degree program in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related field. In addition to the qualifications below, you'll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter. At least 1 year of experience developing software in C++, Python, Compute Unified Device Architecture, Heterogeneous-computing Interface for Portability, Triton, or a comparable high-performance computing or accelerator programming environment. Authorship or co-authorship of at least one peer-reviewed publication, preprint, open-source project, or equivalent research artifact in computer systems, machine learning systems, high-performance computing, computer architecture, or a related field. Experience with performance analysis, benchmarking, or optimization of artificial intelligence, high-performance computing, or distributed systems workloads. Experience with graphics processing unit, accelerator, or low-level systems programming, including kernel development or performance tuning. Experience with machine learning frameworks such as Python Tensor Library, Just After Execution, or TensorFlow. Experience with compiler technologies, code generation, runtime systems, or programming languages. Experience with distributed training or inference systems and communication libraries such as Message Passing Interface, NVIDIA Collective Communications Library, or similar technologies. Experience developing analytical or empirical performance models for computing systems. Experience contributing to open-source software projects related to artificial intelligence systems, compilers, high-performance computing, or computer architecture. Demonstrated research excellence through publications at leading conferences or journals in systems, architecture, machine learning, or high-performance computing.