Research Assistant - Computer Vision for Autonomous Vehicles

University - Computer science
Match Rate
?
Stage
Ph.D
Duration
36 month
Fund
0
Fee
0
Deadline
Dec 12, 2024
Start
Mar 11, 2025

About the position

The development of safe and reliable autonomous vehicles (AVs) hinges on robust computer vision (CV) systems. This research project explores novel CV techniques for enabling AVs to perceive their surroundings and make informed decisions. The successful candidate will delve into various aspects of computer vision for autonomous driving, including:

The candidate will be involved in:

Exam Requirements

IELTS
Listening
6.5
Reading
6.5
Writing
6.5
Speaking
6.5
Overall
6.5

Research Interests

  • Work with Professor Thomas on a research project exploring computer vision techniques for autonomous vehicles.
  • Develop and implement algorithms for object detection, scene understanding, and path planning for self-driving cars.
  • Contribute to the collection and annotation of large-scale driving datasets.
  • Evaluate the performance of computer vision systems in simulated and real-world environments
  • Assist in writing research papers and presentations for publication at conferences and workshops.

Duties and Responsibilities

  • Machine learning
  • Natural language pro
  • Robotics
  • Computer vision
  • ML

Other Requirements, Additional Info

• Strong foundation in computer science with a focus on computer vision and deep learning. • Experience with computer vision libraries like OpenCV or PyTorch. • Programming skills in Python and familiarity with robotics platforms (desirable). • Understanding of sensor fusion techniques and machine learning for autonomous systems. • Excellent written and verbal communication skills. • Strong foundation in computer vision algorithms and deep learning architectures for CV tasks.
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Professor
escholarlink

Dr. Sarah Thomas

Professor
Bio

Sarah Thomas is a Professor of Computer Science at Stanford University. She received her PhD in Computer Science from MIT in 2004. Her research interests include machine learning, artificial intelligence, computer vision, robotics, and natural language processing. She has published over 100 papers in top academic conferences and journals. She has also received several awards for his research, including the ACM SIGKDD Innovation Award, the NSF CAREER Award, and the Google Faculty Research Award. Professor Thomas is a passionate teacher and has won numerous teaching awards. She is also an active member of the computer science community and has served on several program committees and editorial boards. She is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and the Institute of Electrical and Electronics Engineers (IEEE).