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UU Student - Computer
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|Job Title||UU Student - Computer|
|Working Title||Machine Learning Analyst- Student Intern|
|Patient Sensitive Job Code?|
|Type||Non Benefited Staff / Student|
|Standard Hours per Week||19|
|Full Time or Part Time?||Part Time|
|Work Schedule Summary||
M-F, hours to be arranged.
|Is this a work study job?||No|
|Department||00417 - UIT - ACS|
|City||Salt Lake City, UT|
|Type of Recruitment||External Posting|
|Pay Rate Range||$12.00/hr.|
We seek highly motivated students to help support the University Support Services group within the University Information Technology department. This opportunity will focus on developing predictive models, tools, and technology to enable the University to support machine learning initiatives.
AboutUIT: University Information Technology (UIT), the central IT service provider for campus, reports to the Chief Information Officer and is responsible for many of the University of Utah’s most critical common IT resources including the campus network; the Campus Information Services (CIS) portal; UMail, telephone, and online collaboration services; high performance and research computing; information security; teaching and learning technologies; software licensing; and a host of other systems and services. For more information aboutUITvisit http://www.it.utah.edu.
About the University: Located in Salt Lake City, in the foothills of the Wasatch Mountains, the University of Utah is the flagship institution of the State of Utah’s system of higher education and a member of thePAC-12 Conference. Salt Lake City combines the amenities of a major metropolitan area of more than one million people with the friendliness and ease of living of a small, Western city. Seven major ski resorts are within an hour’s drive from campus, and opportunities to pursue activities from biking to hiking to fishing abound. Salt Lake is also home to the Utah Symphony and Opera, the Utah Ballet, several professional sports teams, and a wide range of other cultural and recreational activities. http://www.employment.utah.edu/staff/work.php
The incumbent will work on various technical activities such as documentation, data analysis and visualization, data science, and predictive model development. The incumbent must also assist in championing the use of a coherent development framework, such as KDD, for data selection, pre-processing, transformation, and mining in addition to model selection, interpretation, and performance outputs.
Must be a current University of Utah Student.
Preference will be given to students with related technical coursework and/or professional experience.
Candidates will be expected to have advanced knowledge of high-dimensional, multivariate statistical analysis techniques and understand how to develop, train, and test various supervised and unsupervised learners including: classification and association algorithms, time series and regression models, and clustering and feature selection algorithms. Knowledge of ensemble learning techniques, approaches to model selection and performance measurement, and residual analysis are required. Knowledge of Oracle, Cloudera (Apache Hadoop and related projects), Spark APIs, and Docker/Kubernetes deployments are big pluses. Project management, relational database analysis, and advanced relevant programming skills (i.e., R, Python,SQL, etc.) are a plus. Knowledge of mathematical optimization using Python or Matlab are a plus. Candidates must possess appropriate computer skills, excellent written and verbal communication skills, and a high level of interest and initiative in learning new technologies. Successful candidate must have a positive attitude and focus on solving issues.
|Special Instructions Summary|
The University is a participating employer with Utah Retirement Systems (“URS”). Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS’ post-retirement rules and restrictions. Please contact Utah Retirement Systems at (801) 366-7770 or (800) 695-4877 or University Human Resource Management at (801) 581-7447 if you have questions regarding the post-retirement rules.
Posting Specific Questions
Required fields are indicated with an asterisk (*).
- University of Utah Web Page
- Internet: search engine, online job board, etc
- University of Utah employee referral
- Career Services/Campus Job Fair
- Community/Government Agency
(Open Ended Question)
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