Graduate Research Assistant (Computer Science / AI)

BASE Research Lab — School of Computing, Southern Illinois University Carbondale

Open Position50% FTEImmediate Joining — Fall 2026 & Spring 2027

The Bridging AI, Systems, and Environment (BASE) Research Lab at Southern Illinois University Carbondale is seeking a highly motivated Graduate Research Assistant (50% FTE) with a strong background in Artificial Intelligence, Machine Learning, Deep Learning, and Computer Vision to support interdisciplinary research and educational technology development efforts. The successful candidate will work closely with Dr. Khaled Ahmed and graduate researchers on cutting-edge AI applications involving large language models, intelligent tutoring systems, and advanced deep learning techniques.

Responsibilities

Collect, preprocess, and curate datasets from educational, scientific, and domain-specific resources.
Develop, train, fine-tune, and evaluate Large Language Models (LLMs) and AI systems.
Implement parameter-efficient fine-tuning methods such as LoRA and related approaches.
Design and develop web-based AI applications and user interfaces.
Create benchmarking and evaluation pipelines for AI model assessment.
Collaborate with interdisciplinary teams to support research, development, and deployment activities.
Prepare technical documentation, reports, and research publications.

Required Qualifications

Current enrollment in an M.S. or Ph.D. program in Computer Science.
Preference will be given to students pursuing the thesis option and actively conducting research toward an M.S. thesis or Ph.D. dissertation.
Strong programming skills in Python.
Experience with PyTorch, TensorFlow, or similar deep learning frameworks.
Knowledge of machine learning, deep learning, and transformer architectures.
Familiarity with Linux environments, Git, and software development practices.
Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

Deep Learning & Computer Vision

Experience with Convolutional Neural Networks (CNNs) for image classification, object detection, image segmentation, and feature extraction.
Experience with Vision Transformers (ViT) and transformer-based computer vision architectures.
Experience with object detection and segmentation models such as YOLO, Faster R-CNN, Mask R-CNN, DETR, or related frameworks.
Experience with multimodal AI, Vision-Language Models (VLMs), and image understanding systems.
Experience in medical imaging, agricultural AI, remote sensing, intelligent perception, or related applications.

Large Language Models & Generative AI

Experience with LLMs, transformer models, prompt engineering, and Retrieval-Augmented Generation (RAG).
Experience fine-tuning foundation models using LoRA, QLoRA, PEFT, or similar techniques.
Knowledge of Natural Language Processing (NLP), generative AI, and conversational AI systems.
Experience with model evaluation, explainability, uncertainty estimation, and performance benchmarking.

Benefits

This position offers opportunities to:

Gain hands-on experience with state-of-the-art AI technologies.
Develop expertise in LLMs, computer vision, and transformer-based systems.
Collaborate on interdisciplinary research projects.
Contribute to peer-reviewed publications and conference presentations.
Work within an active research environment focused on innovative AI solutions.

Application Materials

Interested applicants should submit the following to Dr. Khaled Ahmed ([email protected]):

1Curriculum Vitae (CV)
2Statement of research interests and relevant experience
3Unofficial transcripts
Apply by Email

Learn more about our lab on the Projects and Join Our Lab pages.