Open Source Toolbox for Analyzing Frequency Following Responses (FFRs) - OSPO Spring Internship Program
Apply now(opens in a new window) Job No: 509737 Division/Organization: Office of the Vice Chancellor for Research Department: Data Science Institute Job Type: UW Student Jobs Remote Eligbility: Partially Remote Location: MCARDLE BUILDINGSalary/Wage Range or Lump Sum: $15.00-17.00 Job Categories: Interpersonal Communication, Critical Thinking/Problem Solving, Digital Technology, Teamwork/Collaboration, Professionalism/Work Ethic, Information Technology and Computers, STEM, Data Analysis
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.
Knowledge, Skills & Abilities :
Python, Pytorch, TensorFlow, signal processing, Deep learning, pyQt, problem solving
Position Summary/Job Duties:
The aim of this project is to develop an open source toolbox for analyzing frequency following responses (FFRs) to speech using a standardized pipeline and AI based approaches. FFRs are non-invasive neural responses to speech sounds that can be obtained by electroencephalography. The FFRs are phase-locked neural responses emerging from the auditory brainstem and cortex. The FFRs are extensively used across different populations, such as individuals with Autism, phonological disorders, dyslexia, aging, etc., to track the integrity of auditory processing in the brain. While the FFRs provide promising non-invasive snapshot of auditory processing, the methods used to analyze FFRs across different studies are not consistent. Further, researchers working in this field are still using older techniques to analyze FFRs, and make meaningful interpretations about computational mechanisms underlying speech processing. The advances in data analyses in FFR have been monumental in the past 3-4 years. However, access to such tools is limited only to a few labs, and also rely on extensive computational knowledge by the user. This project aims to develop an open-source toolbox for FFR analysis that would be accessible to researchers with a varied range of expertise. The toolbox will be made available both as scripts and gui to be used by beginners and advanced users alike. This will be a one of a kind toolbox that incorporates a range of feature extraction and AI-based models to decode the stimulus features encoded in the FFRs. These models are designed to be neurophysiologically interpretable while being extremely robust for applications in a variety of situations. The software development is underway. We have a rough gui ready. We have developed 10 different AI-based models to analyze the FFRs. Future work is aimed at fine-tuning these models and integrating them in the gui we are developing. The models will be able to run individual-specific and generic models to derive interpretable features from the FFRs.
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/
Advertised: November 17, 2025 09:00 AM Applications close: November 26, 2025 11:55 PM
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