Foundation Models for Autonomous Driving – Research Intern

Job Description

• Conduct advanced research and engineering in multimodal LLMs, 3D perception, knowledge distillation, and diffusion models to address challenges in autonomous systems. 

• Apply research results to real-world applications with high quality implementation 

• Integrate the resulting system/software into existing Bosch platform 

• Summarize research findings in high-quality paper and/or patent submissions 

Qualifications

Required:

• Ph.D. student in Computer Science or related fields (Must be a current student)  

• Hands-on experience on developing computer vision and machine learning algorithms with focus on at least two of the following areas: multimodal foundation  models, diffusion models, detection/segmentation, 3D scene understanding, autonomous driving , and sensor fusion. 

• Solid Python skills and proficient with libraries such as MMCV, and PyTorch. 

Preferred:

• Publication record in top venues including CVPR, ICCV, ECCV, ICML, ICLR, and  NeurIPS. 

• Familiar with SOTA vision and learning methods of multimodal LLMs, diffusion models, Diffusion Models, knowledge distillation, and so on.  

• Able to work independently, has strong research and problem-solving skills 

• Strong background in math and statistics is a plus. 

• Good communication and teamwork skills