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Provost Research Computing Center

About the Department

The University of Chicago Research Computing Center (RCC), a unit in the Office of Research, provides high-end research computing resources to researchers at the University of Chicago. It is dedicated to enabling research by providing access to centrally managed High-Performance Computing (HPC), storage, and visualization resources. These resources include hardware, software, high-level scientific and technical user support, and the education and training required to help researchers make full use of modern HPC technology and local and national supercomputing resources. The Office of Research oversees the conduct of sponsored research, research program development, and contract management functions.

Job Summary

The job develops software to support the data acquisition, ingestion, and integration for research projects. Assists in the development of user interfaces and scalable back-end services to automate and accelerate the scientific output of multi-institutional research projects.

The Research Computing Center at the University of Chicago seeks a highly motivated Computational Scientist-Computational Biology that will support the Program in Computational Biology (PCB), lead by Matthew Stephens in the department of Human Genetics, with implementing novel computational and statistical methods for analysis of biological data. The PCB is a group of faculty, students and postdoctoral researchers at the University of Chicago who work on problems related to computational biology. The person in this role will serve as a bridge between research groups, and a technical domain expert in supporting and advising PCB members on computational aspects of their research as well as how to use all the RCC resources available to them. The successful candidate will join a team of computational scientists who are playing a key role in enabling research at the University of Chicago.

Responsibilities

• Assist with compiling, debugging, optimizing, profiling, and porting codes on RCC HPC systems.
• Assist with improvements, scaling, parallelization, and load balancing of large-scale research codes. Assist with maintaining community codes.
• Assist with writing of code, and relevant scripts.
• Develop, install, and test scientific software in support of research goals.
• Work with PCB faculty and their research groups, and respond to their enquiries, to enable them to fully utilize the University and national computational resources for their research.
• Collaborate with RCC peers and vendor partners to enable PCB to leverage all the expertise available at the RCC and beyond.
• Develop, contribute to, and/or help to document computational software products, including data processing and data organization.
• Promote software development best practices and reproducibility of computational research in PCB research groups and the wider UChicago community.
• Support the optimization of the use of their models to efficiently use RCC\'s various resources.
• Work with researchers to improve their coding skills through dedicated hands-on workshops, education, and advice.
• Design, create, and present tutorials, hands-on workshops, and documentation.
• Help researchers with grant proposals with a strong computation component.
• 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 throu h quality control reviews.
• Perform other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.

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Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifications

Education:

• PhD in Genetics, Statistics, Computer Science, or related field.

Technical Skills or Knowledge:

• Proficiency in R programming language.
• Proficiency in a scripting language such as Python.
• Working knowledge in one of more programming language and libraries such as C++, C, Julia, MPI, OpenMP, etc.
• Linux/Unix.
• Software design and development methodologies and best practices.
• Installing and tuning scientific applications software.

Preferred Competencies

Understand and translate researchers\' scientific goals into computational requirements.

Work well wit