Current opportunities: 1
1. COMPUTATIONAL AND DATA SCIENCE RESEARCH SPECIALIST – 127110
Filing Deadline: Tue 1/2/2024
DESCRIPTION
The Computational and Data Science Researcher applies skills as a seasoned, experienced IT research professional. Uses computational, computer science, data science, and CI software research and development principles, with relevant domain science knowledge where applicable, along with professional programming concepts for medium-sized projects or portions of larger projects.
Collaborates with students, faculty, and postdoctoral researchers to develop modeling, data processing, and visualization tools for integrated research efforts. Responsibilities include (but is not limited to) the development of tools for model coupling, data format translation, uncertainty quantification, deployment of large model ensembles, containerized workflows, climate downscaling, and web delivery of climatic datasets. Port existing models to UCSD HPC resources or work in partner-based external HPC environments. Train students, postdocs, and faculty how to use the project-specific HPC resources. Modify existing code and develop new code for research projects. Optimize model code and structure for computational efficiency. Works on algorithm development, optimization, programming, performance analysis and / or benchmarking assignments of moderate scope where the tasks involve knowledge of Marine Science, Oceanography, and Environmental Science. Contribute technical information to publications in peer-reviewed journals.
QUALIFICATIONS
- Bachelor’s degree in Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience.
- Proficient in scientific programming and experience with model development and data analysis in at least two languages (FORTRAN, Python, Matlab, R).
- Understanding of climate dynamics, ocean physics, biogeochemical cycling, and/or marine food-web dynamics.
- Intermediate knowledge of HPC / data science / CI.
- Advanced skills, and demonstrated experience associated with one or more of the following: HPC hardware and software power and performance analysis and research, design, modification, Implementation and deployment of HPC or data science or CI applications and tools.
- Strong quantitative skills.
- Familiarity with code repositories (e.g. git) and Pangeo tools (e.g. JupyterLab, Xarray, Dask, netCDF).
- Experience working in (or administering) high-performance Linux supercomputing environments and with additional relevant languages such as C/C++, Javascript, or NCL.
- Proven skills and experience in independently resolving broad computing / data / CI problems using introductory and / or intermediate principles.
- Thorough experience working in a complex computing / data / CI environment encompassing all or some of the following: HPC, data science infrastructure and tools / software, and diverse domain science application base.
- Proven ability to understand research computing / data / CI needs, mapping use cases to requirements and how systems / software / infrastructure can support those needs and meet the requirements. Demonstrated ability to develop and implement such solutions.
- Demonstrated broad experience in one or more of the following: optimizing, benchmarking, HPC performance and power modeling, analyzing hardware, software, and applications for HPC / data / CI.
- Demonstrated ability to contribute research and technical content to grant proposals.
- Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines.
- Proven ability to successfully work on multiple concurrent projects.
- Demonstrated experience and ability to collaborate effectively with all levels of staff; technical, students, faculty and administrators Ability to collaborate effectively in a team environment.
- Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences.
- Demonstrated ability to regularly interface with management.