SING 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.
The Research Computing Center (RCC) seeks a highly motivated Computational Scientist to work closely with faculty and researchers in the Chicago Booth School of Business (Chicago Booth) at The University of Chicago.
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 person in this position will serve as a technical domain expert, supporting and advising faculty on high-end computing and machine learning techniques for big data analysis in their research and grant writing.
- Central knowledge resource for faculty and researchers in Chicago Booth, working closely with faculty to identify, develop, and implement useful computational methods and resources that advance their research.
- Assists in the development, implementation, and improvement of application software and methods that can be utilized in analyzing and interpreting data in Chicago Booth. Assists with compiling, debugging, optimizing, profiling and porting codes on RCC compute and storage resources.
- Designs tutorials, hands-on workshops, and documentation for researchers and students in Chicago Booth with the help and coordination of other RCC staff.
- Keeps abreast of new developments in high-end computing and pro-actively introduces them to the faculty.
- Helps faculty with grant proposals by contributing sections of the proposal that describe the interplay between their research and high-end computing resources.
- Assists researchers with data management implementations and compliance to funding agencies requirements.
- Dedicates a portion of time on research projects or activities for professional development, as approved.
- Participates in the product development life cycle, providing professional assistance to the design of front-end applications and database systems back-end schema. Analyzes high-level system specifications and makes sure that all application development standards are met.
- 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.
Minimum requirements include a college or university degree in related field.---
Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.---
- Ph.D., preferably in the fields of economics, finance, behavioral science, statistics, applied math or computer science.
Technical Skills or Knowledge:
- Experience applying computer science methodologies in economics, financial management or similar field.
- Proficiency with machine learning techniques and algorithms.
- Broad programming skills to support analysis efforts in multiple programming environments.
- Numerical computing experience using statistical programming packages, such as Python, Matlab or R.
- Fluency in data manipulation and analysis.
- Experience in a UNIX-based programing environment.
- Proficiency with applied statistical skills, such as distributions, statistical testing, regression, etc.
- One or more programing languages (such as C++, C, Fortran, Stata, Julia, etc.).
- Data visualization tools, such as D3 or GGplot.
- Parallel computing experience with MPI and OpenMP.
- Familiarity with Natural Language Processing (NLP) methods, recent trends in deep learning and hands-on experience with various Deep Learning methods and technologies such as PyTorch.
- Exposure or experience in any of the following a plus: Hadoop, Pig, Hive, SQL coding, relational database structures and query techniques.
- Understand and translate researchers' scientific goals into computational requirements.
- Excellent communications and presentation skills.
- Function as part of an interactive team while demonstrating self-initiative to achieve project's goals and research computing center's mission.
- Resume/CV (required)
- Cover letter (preferred)
When applying, the document(s) MUST
be uploaded via the My Experience
page, in the section titled Application Documents
of the application.Job Family
Individual ContributorFLSA Status
MonthlyScheduled Weekly Hours
YesRequires Compliance with University Covid-19 Vaccination Requirement
YesDrug Test Required
NoHealth Screen Required
NoMotor Vehicle Record Inquiry Required
Employees must comply with the University's COVID-19 vaccination requirements. More information about the requirements can be found on the University of Chicago Vaccination GoForward.
The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national or ethnic origin, age, status as an individual with a disability, protected veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.
Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.
We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.
All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.
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