1. Collaborate with faculty and researchers to provide scientific computational expertise to enhance efficiency of research algorithms.2. Interface with faculty to solicit requirements on how best to enhance the daily operations of the Yale's Center for Research Computing (YCRC). 3. Work with the HPC engineering team to implement these operational enhancements.4. 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. This includes: a. Software installation and support of various scientific software packages. b. Support of research groups' computational research through consultation and design of software and systems. c. Parallel programming and performance tuning. d. Assistance with data management and sharing. e. Troubleshooting users' computational problems.5. Investigate new computing technologies (in areas such as hardware, software, and networking, depending on the candidate's interests and expertise).6. Develop and deliver training programs, seminars, and other outreach activities to a diverse community of faculty, students, and others sharing a common interest in advanced computing and data processing technologies for research.  Training will include basic and advanced programs in HPC and data science.

Required Skill/ability 1:  Extensive ability working in Linux environment.

Required Skill/ability 2:  Mastery of programming in at least one language such as Python or C.

Required Skill/ability 3:  knowledge of software building and installation: e.g. make, autoconf, etc.

Required Skill/ability 4:  Demonstrated ability to juggle multiple projects/collaborations simultaneously.

Required Skill/ability 5:  Excellent written and oral communications skills

Preferred Education:  

Experience with building and tuning AI systems. Experience with GPUs and HPC clusters.

AI tools: TensorFlow, Keras, PyTorch, Large Language Models

Computing languages such as: C, Python, Matlab, R

High performance computing in a linux environment

Software tools: Docker, Apptainer, Slurm, MPI, Jupyter, EasyBuild, conda

Teaching of courses, workshops, consulting