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.
--- Work Experience:
Minimum requirements include knowledge and skills developed through --- 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 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) MUSTbe 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
Posting Statement
The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national or ethnic origin, age, status as an individual with a disability, military or 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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