Research Assistant

Department
 

Provost CASE At-Large

About the Department
 

The Office of Research works with faculty and deans to support and enhance research funding and manage large-scale research infrastructure such as University Research Administration (URA) and the University of Chicago Consortium for Advanced Science and Engineering (CASE), the Office of Research Safety, Research Computing Center, and Research Development Support.

Job Summary
 

The Research Assistant will work closely with the principal investigator (Dr. Daniel Maldonado, Scientist-at-Large, CASE, The University of Chicago, Assistant Scientist, Mathematics and Computer Science Division, Argonne National Laboratories) to carry out grant-funded projects focused on developing randomized algorithms and their implementation, developing uncertainty quantification algorithms, and developing statistical techniques to model data. The successful candidate will contribute to the development of a cutting-edge cyberinfrastructure for rapid implementation and reproducible comparison of randomized linear algebra algorithms, as well as the creation of novel methodologies for optimization under non-Gaussian probabilistic constraints. The Research Assistant will play a key role in advancing the state-of-the-art in these areas, with a focus on statistical modeling, uncertainty quantification, and the development of robust and reliable algorithms for complex, real-world applications.

Responsibilities

• Supports projects and carries out activities to advance goals and objectives.

• Conducts scientific literature reviews.

• Collaborates with Principal Investigator and team to develop and implement novel research algorithms.

• Engages with research community and disseminates research.

• Collects, organizes, and may analyze information from the University's various internal data systems as well as from external sources.

• Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference. Performs maintenance on large and complex research and administrative datasets. Responds to requests and engages other IT resources as needed.

• May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or ad-hoc basis.

• Performs 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 years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifications

Experience:

• At least three (3) years of professional experience writing code in an interpreted language, such as Python or Javascript.

• Experience communicating results through writing and presentations, both in and out of one’s own discipline.

• Knowledge of software development best practices and commonly used tools.

• Demonstrated experience in software engineering, applied machine learning and/or advanced statistical methods.

• Demonstrated record of success working at the intersection of environment, human rights and data science.

• Experience participating in open source software development and significant contributions to open source projects are also highly valued in this role.

• Expertise in probability theory, linear algebra, and statistics.

• Familiarity with data analysis, visualization, and statistical inference techniques.

Technical Skills or Knowledge:

• Proficiency in programming languages such as Python and Matlab.

Application Documents

• Resume (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
 

Research

Role Impact
 

Individual Contributor

FLSA Status
 

Non-Exempt

Pay Frequency
 

Biweekly

Scheduled Weekly Hours
 

40

Benefits Eligible
 

Yes

Drug Test Required
 

No

Health Screen Required
 

No

Motor Vehicle Record Inquiry Required
 

No