Job Description

• Research and develop real time image selection using active/semi-supervised learning strategies for automated scene identification eg. from a fleet vehicle.
• Benchmark developed solution against state-of-the-art methods from the literature.
• Collaborate with other deep learning teams across business units for joint development.
• Integrate the proposed solutions onto Bosch hardware.
• Summarize research findings in high-quality paper and/or patent submissions.

Qualifications

Required:

• Pursuing a PhD or Master degree in Computer Science, Data Science, Electrical Engineering, or Mathematics
• Solid understanding of fundamental and cutting edge computer vision and deep learning
• Strong general programming skills with Python
• Strong deep learning programming skills with TensorFlow, Keras, or PyTorch
• Ability to work independently
• Excellent communication skills

Desired:

• Solid knowledge and experience with semantic segmentation, object detection e.g., YOLO, SSD, RetinaNet etc.
• Solid knowledge and experience with active learning, semi-supervised or weakly supervised learning methods.
• Publication record in top AI conferences (CVPR/ICCV/ECCV/NIPS/ICLR/AAAI, etc)

• Degree level: PhD or Master – Must be a current student or recent graduate (less than 1 year)
• Duration of Internship: 12-24 weeks
• Start Date: Summer/Fall 2021

By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.

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)