How to Apply
In addition to your application on careers.umich.edu, please email the following to [email protected] with the subject line:
Temporary RA - Neurosymbolic Web Filtering (SMILES Lab)
- Resume or CV
- Links to relevant code repositories, projects, or previous research
Job Summary
The Secure Modeling and Intelligent Learning Systems (SMILES) Lab at the University of Michigan-Flint is hiring a part-time research assistant for a temporary, hourly-paid position. The project focuses on developing neurosymbolic multimodal web filtering systems, combining neural models with symbolic reasoning to detect, analyze, and filter content across text, images, video, and audio streams.
This role is open to both UM-Flint students and external candidates, including those interested in gaining experience in hybrid AI, explainable systems, and content moderation technologies.
Responsibilities*
- Develop and test APIs to serve neurosymbolic and multimodal models.
- Deploy machine learning models on cloud platforms (e.g., AWS, GCP) using containers and scalable services.
- Design and implement knowledge graphs to enable structured reasoning over web content.
- Integrate retrieval-augmented generation (RAG) pipelines to enhance contextual understanding.
- Build and evaluate hybrid AI systems combining neural networks with logic-based frameworks.
- Prepare and manage multimodal datasets (e.g., text, image, video, audio) for training and evaluation.
- Support benchmarking, experiment tracking, and documentation.
- Participate in weekly lab meetings and contribute to collaborative research outputs.
Required Qualifications*
- Graduate student at the University of Michigan-Flint or other accredited academic institution.
- Strong programming experience in Python; proficiency with PyTorch .
- Familiarity with foundation models (e.g., CLIP, BERT, GPT) and symbolic reasoning tools (e.g., Prolog, RDF, SPARQL).
- Experience or interest in RAG frameworks and vector-based retrieval systems (e.g., FAISS, Weaviate).
Desired Qualifications*
- Experience with Docker, FastAPI, and cloud environments (AWS or Azure) is highly desirable.
- Self-motivated, detail-oriented, and capable of working both independently and within a team.
Modes of Work
Hybrid
The work requirements allow both onsite and offsite work and an employee has an expected recurring onsite presence. On occasion, the employee may be required and must be available to work onsite more frequently if necessitated by unit leadership or their designee and/or the job requirements.
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.
Additional Information
This position will have an earliest start date of July 5, 2025 and has an end date of 8/22/2025. If employment is to continue into the Fall 2025 semester the employment appointment will be transferred to a GSRA appointment
Background Screening
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.
Application Deadline
Application Deadline: June 25, 2025
Job openings are posted for a minimum of three calendar days. The review and selection process may begin as early as the fourth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U-M EEO Statement
The University of Michigan is an equal employment opportunity employer.