Support applications, software, and tools for research related to climate, geophysical science, atmospheric science, etc.
Assist researchers with compiling, debugging, optimizing, profiling, and porting codes and related applications on RCC HPC compute systems.
Maintain and keep up to date on RCC HPC systems, community codes and software such as WRF, CESM, etc.
Maintain and keep up to date repository of data for and from the climate and earth system science research community.
Support and make available tools and resources to help UChicago researchers understand the strengths, limitations, and applications of the data, as well as software to help researchers analyze and visualize the data.
Consult and interact with faculty and their research groups on a one-to-one basis to enable them to fully utilize the RCC and national computational resources for their scientific research.
Design, create and present tutorials, hands-on workshops, and documentation.
Help faculty with grant proposals by contributing sections of the proposal.
Develops and presents technical training materials and web-based documentation. Ensures timely systems support and updates. Assists in conducting information security assessments and risk analysis of computing environment.
Evaluates past and present technologies to help develop new tools. Ensures all the new tools have been through quality control reviews.
Performs other related work as needed.
Preferred Qualifications
Education:
PhD in Math, Computational Sciences, Earth Science, Soil Science, Environmental Science, geophysical sciences, or related field.
Experience:
Experience writing or contributing to grant proposals strongly preferred.
Must have strong understanding of climate and earth system science as demonstrated by academic record and/or job history.
Technical Skills or Knowledge:
Proficiency in using one or more scientific programming languages such as C/C++, Fortran90, Python, MATLAB.
Experience with scripting languages and visualization software to process, analyze, visualize, and interpret large datasets and dynamical model forecasts strongly preferred.
Experience using ML or AI techniques for Climate or earth system science strongly preferred.
Proficiency in temporal and spatial statistical analysis strongly preferred.
Experience with UNIX programing.
Parallel computing experience with MPI and OpenMP strongly preferred.
Experience with Python (including packages such as pandas, numpy, scikit-learn, etc.), Shell, Git, Docker strongly preferred.
Experience with IDL strongly preferred.
Experience using one or more climate related community codes such WRF, CESM highly strongly preferred.
Experience installing and tuning scientific applications software on high-performance computers highly preferred. Strong software skills under Linux highly strongly preferred.
Experience with HPC compiler optimization techniques and performance analysis and profiling tools strongly preferred.
Experience working with scientific software packages such as NetCDF Climate Data Operators (CDO) and/or NetCDF Operators, strongly preferred.
Preferred Competencies
Excellent interpersonal, verbal, written, and presentation skills.
A broad knowledge of algorithms, programming languages, and libraries.
Ability to understand and translate researchersâ™ scientific goals into computational requirements.
Ability to identify and gain expertise in appropriate new technologies and/or software tools.
Ability to function as part of an interactive team while demonstrating self-initiative to achieve projectâ™s goals and Research Computing Centerâ™s mission.
Demonstrated ability to work collaboratively within cross-functional teams.
Strong analytical skills and problem-solving ability.
Ability to work well with faculty and researchers.
Application Documents
Resume or CV (required)
Cover Letter (preferred)
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