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• If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

JOB DESCRIPTION AND POSITION REQUIREMENTS

We are seeking a graduate research assistant to join an innovative project at the intersection of artificial intelligence and education. This project, led by Dr. Mahfuza Farooque in the School of EECS at Penn State, focuses on developing a personalized recommendation engine for microlearning content. The RA will play a key role in leveraging student performance data to deliver tailored learning experiences. This position is a unique opportunity to contribute to cutting-edge research that can enhance student learning outcomes.

Position Details

• Anticipated Start Date: July 15, 2025
• End Date: December 15, 2025
• Weekly Hours: 20 hours per week (flexible scheduling)
• Compensation: $20 per hour
• Location: Flexible (in-person at University Park, remote, or hybrid arrangement)

The research assistant will be involved in various aspects of the project’s development and evaluation. Key responsibilities include:

• Data Analysis: Assist in collecting and analyzing student performance data to inform the recommendation engine.
• Algorithm Development: Contribute to designing, prototyping, and testing algorithmic models for personalized content recommendations.
• System Evaluation: Support the evaluation of the recommendation engine’s effectiveness (e.g. running experiments or user studies to assess learning outcomes).
• Documentation: Help document the system design, development process, and experimental results for project reports or publications.
• Collaboration: Work closely with the project lead and team, participating in regular meetings and brainstorming sessions.

This role offers hands-on experience in AI and data-driven education technology. The RA will have the flexibility to work on-site or remotely as needed and will gain valuable experience on an interdisciplinary project that bridges computer science and learning science.

Preferred Qualifications

• Enrollment: Must be a current graduate student (Master’s or PhD) in a relevant field (e.g. Computer Science, Data Science, Learning Sciences, Educational Technology, or related).
• Technical Skills: Familiarity with artificial intelligence/machine learning techniques and data analysis. Experience with prog