Project Overview
We are seeking a highly motivated and talented postdoctoral researcher to join our team to spearhead research that explores the development of AI-based tutoring technologies to support interactive learning. One initial example for such learning will involve the development of new AI capabilities to support interactive question answering and explanations for Mathematics concepts, particularly for primary and secondary school students. Research will involve leveraging on and customizing multi-modal large vision language models (VLMs) for problems that require both image and text understanding such as Geometry and Mensuration. This position offers a unique opportunity to contribute to cutting-edge research in AI for Education, with a particular emphasis on creating core interactive learning technologies that enhance student engagement and learning outcomes.
Responsibilities
- Develop and integrate Vision-Language Models (VLMs) like GLLAVA or CLIP into learning workflows and processes.
- Augment state-of-the-art VLMs with domain-specific capabilities, such as concept identification in mathematical problems and incorporation of audiovisual interactive feedback
- Develop techniques to identify a learner’s knowledge gaps and learning style, and enhance AI-based solutions to adapt to such gaps and styles.
- Lead the collection and generation of datasets, including synthetic datasets, and collaborate with local organizations for realistic data.
- Research AI and sensing technologies to assess students' emotional and cognitive states.
- Publish research findings in top-tier conferences and journals in the fields of AI, Education, and Human-Computer Interaction (HCI).
- Mentor graduate and undergraduate researchers and interns involved in related research projects.
Requirements
- Ph.D. in Computer Science, Artificial Intelligence, Educational Technology, or a related field from a reputed academic institution.
- Strong background in machine learning, natural language processing, computer vision or multimedia, with specific expertise in particular multi-modal processing combining language and vision modalities.
- Experience with developing educational technologies or intelligent tutoring systems will be an added advantage.
- Proficiency in programming languages such as Python (Preferred), Java, or C++, and machine learning libraries such as PyTorch (Preferred), Tensorflow.
- Experience with large language models (LLMs) and vision-language models (VLMs), such as Llama, LLAVA, CLIP, or similar, is highly desired
- Experience with finetuning existing VLM/LLMs on different tasks using LoRA or similar techniques.
- Excellent communication skills and the ability to work collaboratively in a multidisciplinary team.
- Proven track record of publishing in reputable academic journals and conferences.
Preferred Qualifications
- Experience with adaptive learning systems and personalized education approaches.
- Familiarity with cognitive science and educational psychology principles.
- Strong problem-solving skills and the ability to innovate in a fast-paced research environment.
To apply, please visit our website at: https://portal.smart.mit.edu/careers/career-opportunities
Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.
