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
Basic:
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
Additional Information
Major(s): Computer Science or related fields
Degree level: MSc. Candidates
Start Date: May, 2025
BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics) Initiatives
FIRST Robotics (For Inspiration and Recognition of Science and Technology)
AWIM (A World In Motion)
The U.S. base salary range for this intern position is $43.00-$66.00 per hour. Within the range, individual pay is determined based on several factors, including, but not limited to, type of degree, work experience and job knowledge, complexity of the role, type of position, job location, etc. Your Hiring Manager can share more details about the specific salary range for this position during the interview process.
By choice, we are committed to a diverse workforce – EOE/Protected Veteran/Disabled.
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