• Job Description

  Req#: 509741

  Department Overview:	The Open Source Program Office (OSPO) is looking to connect interns with meaningful open-source projects as part of a new cohort of the internship program in collaboration with Madison College. During the internship, students will join a mentored open source project, participate in an initial training session, and weekly check-ins with the Open Source Program Office, and learn crucial skills related to managing open source software projects and growing software user communities.
  Anticipated Start Date:	2/2/2026
  Anticipated End Date (If Applicable):	5/1/2026
  Remote Work Eligibility Detail:	Partially Remote
  Anticipated Hours Per Week:	Minimum: 10 Maximum: 15
  Schedule:	Internship work schedules will be established in collaboration with the project mentors, with a general expected commitment of 10-15 hours/week. In addition to the work schedule established with the project lead, interns will participate in a weekly group session with the OSPO for check-ins, trainings, and guest speakers.
  Salary/Wage Range/Lump Sum:	Minimum: $15.00 Maximum: $17.00
  Number of Positions:	1
  Qualifications:	UW-Madison and Madison College undergraduate and graduate students with applicable backgrounds in any field are eligible to apply. Students must be enrolled in a degree program during the calendar year with at least one semester remaining after the internship’s conclusion. Application materials should include: - A one-page cover letter that highlights your qualifications based on skills identified in the project listing and your interest in open source broadly. - A resume that includes your name, school email address, phone number, field(s) of study (major, minor, degree, certificate), relevant coursework, extracurricular activities, expected graduation date, relevant sample work (ex: GitHub link, personal website, etc.) and any relevant work or research experience. -The names and contact information of three references. Submit a resume, cover letter, and three references as part of your application.
  Knowledge, Skills & Abilities:	Knowledge of R and version control with Git is required as is a willingness to learn C++. Of course, previous experience with C++ would be beneficial. Familiarity with l1 regularization would be useful but is not strictly necessary.
  Position Summary/Job Duties:	The LASSO (i.e., l1 regularization) is one of the most important methods in modern statistics and machine learning, enabling practitioners to fit high-dimensional models with more latent parameters than observations. From the linear models that underpin genome-wide association studies to deep neural network, l1 regularization is an indispensable tool in modern data science. While some of the LASSO's popularity and ubiquity can be attributed to its strong empirical performance and its favorable theoretical properties, a far larger share is due to the availability of easy-to-use open-source software implementations, notably the glmnet package in R. Despite its success, the LASSO is known to struggle in settings with correlated features and in more complicated problems involving multiple, possibly dependent outcomes. Over the last decade has seen, an alternative penalty, known as the spike-and-slab LASSO has emerged and proven to work somewhat better than the LASSO in these challenging settings. Unlike the LASSO, which shrinks large and small signals towards zero at exactly the same rate, the spike-and-slab LASSO automatically and adaptively shrinks smaller signals to zero less aggressively than larger signals. This often yields superior variable selection, lower estimation error, and increased predictive accuracy. Unfortunately, development of the spike-and-slab LASSO has occurred across several R package, which are not inter-operable. This project aims to unify these implementations into a new R package, built around a single, shared C++ library. It will also involve creating a package website (e.g., with **pkgdown**) containing documentation and vignettes explaining how to use the main functions. Ultimately, the goal is to create something akin to **glmnet** and its website (https://glmnet.stanford.edu/index.html) but for spike-and-slab regularization. The project will not involve developing or deriving any new statistical algorithms. Instead, it will consist primarily in re-factoring existing C++ code, developing user-facing R wrapper functions, documentation, and creating vignettes demonstrating the main operations.
  Physical Demands:	Interns are expected to be able to sit for extended periods. Specific physical demands will be discussed with mentors during the interview process.
  Institutional Statements:	Equal Employment Opportunity Statement: UW-Madison is an Equal Employment, Equal Access Employer committed to increasing the diversity of our workforce. Institutional Statement on Diversity: Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals. The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background-people who as students, faculty, and staff serve Wisconsin and the world. For more information on diversity and inclusion on campus, please visit: diversity.wisc.edu Accommodation Statement: If you need to request an accommodation because of a disability, you can find information about how to make a request at the following website:https://employeedisabilities.wisc.edu/disability-accommodation-information-for-applicants/

• About the company

  The University of Wisconsin is a top-ranked research institution located in Madison, Wisconsin, providing exceptional education opportunities to undergraduates, graduate and professional students.

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