Contact

📢 신입생 입시 안내 (Graduate Admissions)

본 연구실의 석·박사과정 신입생은 KAIST 대학원 입학전형을 통해 선발하며, 문화기술대학원(GSCT), 로봇학제(Robotics Program), 미래차학제(Division of Future Vehicle)를 통해 지원할 수 있습니다.

Prospective M.S. and Ph.D. students must apply through the official KAIST graduate admissions process to the Graduate School of Culture Technology (GSCT), Robotics Program, or Division of Future Vehicle.

🚀 Open Positions

본 연구실은 인턴, 석·박사과정 학생 및 박사후연구원을 상시 모집하고 있습니다.

We welcome applications year-round from research interns, prospective M.S. and Ph.D. students, and postdoctoral researchers in the following research groups.

👁️🤖 3D Vision & Physical AI

Research Areas

• 3D visual perception, reconstruction, and spatial understanding
• Robot policy learning and planning for real-world environments
• Humanoids, manipulators, and mobile manipulators

Requirements

• Strong background in computer vision, machine learning, robotics, or related fields
• Proficiency in Python and PyTorch
• Hands-on experience in one or more of the following:
  • Camera calibration and 3D vision pipelines
  • Isaac Lab–based robot simulation and learning
  • Robot learning, planning, or control
• C++ and ROS/ROS2 experience is preferred

🎨 Multimodal & Generative AI

Research Areas

• Multimodal understanding and generation
• Image and video generation and editing
• Vision-language models and world models

Requirements

• Strong background in machine learning, computer vision, NLP, or related fields
• Proficiency in Python and PyTorch
• Experience with transformers, diffusion/flow models, or multimodal models
• Experience in large-scale model training and evaluation is preferred

📝 How to Apply

연구실 합류를 희망하는 분은 관심 있는 연구 그룹을 명시하여 아래 자료를 이메일로 보내주시기 바랍니다.

• CV
• 성적증명서(학생 지원자)
• 관심 연구 분야 및 관련 연구 경험에 대한 간단한 소개

If you are interested in joining our lab, please indicate your preferred research group and email the following materials:

• CV
• Academic transcripts for student applicants
• A brief description of your research interests and relevant experience

📧 Email: rvlab [at] kaist.ac.kr