Part-time Research Assistant – Advancing AI Education with Foundation

Other, Hybrid/Flexible Work Arrangement

Drexel University

Drexel University in Philadelphia, PA is an academically comprehensive and globally engaged urban research university, dedicated to advancing knowledge and society and to providing every student with a valuable, rigorous, experiential,...

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Job Summary

Dr. Kaidi Xu in the Computer Science department in the College of Computing & Informatics seeks a motivated part-time research assistant to join a project that explores the role of foundation models in transforming AI education. This research investigates how large-scale models can support teaching, personalize learning experiences, and automate assessment in AI and machine learning coursework.

Essential Functions

  • Support the design and adaptation of foundation models (LLMs, vision-language models) for educational applications
  • Prepare, clean, and organize diverse datasets (text, image, code) tailored for instructional use 
  • Conduct experiments involving model fine-tuning, evaluation, and prompt optimization 
  • Summarize experimental outcomes and contribute to writing research articles, technical reports, and presentation materials
  • Collaborate regularly with faculty, researchers, and peers through meetings and project updates 

Required Qualifications

  • Minimum of Bachelor's Degree

Preferred Qualifications

  • Experience adapting foundation models for education, edtech, or learning analytics contexts
  • Knowledge of prompt engineering, retrieval-augmented generation (RAG), or model evaluation metrics
  • Background in AI/ML education, human-computer interaction (HCI), or cognitive science

Location

  • Hybrid/Flexible Work Arrangement

Additional Information

This is a Part-Time temporary position classified as Non-Exempt. The offered pay is based on the successful candidate’s qualifications and experience, department budget, and an internal equity review.

For information about benefits, please review Drexel’s Per Diem/Casual/Temporary Benefit Fact Sheet.

Special Instructions to the Applicant
Please make sure you upload your CV/resume and cover letter when submitting your application.

A review of applicants will begin once a suitable candidate pool is identified.

 

 

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Computer Science Engineering LLMs Machine Learning Prompt engineering RAG Research Teaching

Perks/benefits: Career development

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