Computational Research Support Analyst (AI/GPU)

Yale University - New Haven, CT

Full-time - Entry Level

New Haven, CT

Educational Services

About the position

The Computational Research Support Analyst at the Yale Center for Research Computing plays a crucial role in providing support for research initiatives focused on Artificial Intelligence, particularly in GPU computing and large language models. This position involves collaborating with faculty and researchers to enhance research efficiency, offering technical support, and developing training programs for users across various departments. The role is integral to the expansion of AI resources at Yale, supporting a diverse range of research interests and computational abilities.

Responsibilities

• Collaborate with faculty and researchers to provide scientific computational expertise to enhance efficiency of research algorithms.
• Interface with faculty to solicit requirements on how best to enhance the daily operations of the Yale's Center for Research Computing (YCRC).
• Work with the HPC engineering team to implement operational enhancements.
• Provide technical support, computing assistance, and training to YCRC users primarily in the university's main campus departments in the natural and social sciences and engineering.
• Support research groups' computational research through consultation and design of software and systems.
• Investigate new computing technologies in areas such as hardware, software, and networking.
• Develop and deliver training programs, seminars, and other outreach activities to a diverse community of faculty, students, and others.

Requirements

• Bachelor's degree in a scientific or computational field plus two years of academic or scientific industry experience.
• Extensive ability working in Linux environment.
• Mastery of programming in at least one language such as Python or C.
• Knowledge of software building and installation: e.g. make, autoconf, etc.
• Demonstrated ability to juggle multiple projects/collaborations simultaneously.
• Excellent written and oral communications skills.

Nice-to-haves

• Experience with building and tuning AI systems.
• Experience with GPUs and HPC clusters.
• Familiarity with AI tools: TensorFlow, Keras, PyTorch, Large Language Models.
• Proficiency in computing languages such as: C, Python, Matlab, R.
• Experience in high performance computing in a Linux environment.
• Knowledge of software tools: Docker, Apptainer, Slurm, MPI, Jupyter, EasyBuild, conda.
• Experience in teaching courses, workshops, or consulting.