Description: The position focuses on applying machine learning and decision support to analyze and enhance driver situational awareness for next generation advanced driver assistance systems.
- Participate in ideation, formulation, and definition of the situational awareness problem in the driving scene domain.
- Develop computational models of driver gaze behavior.
- Develop algorithms for spatial and temporal model of traffic scene saliency with objects, semantics, and low-level cues.
- Develop and evaluate metrics to verify the reliability of the proposed algorithms.
- Conduct user experiments using our advanced test vehicles equipped with cameras, LiDAR, CAN-bus, and driver monitoring sensors.
- Participate in sensor calibration/synchronization, data collection and data management.
- Contribute to a portfolio of patents, academic publications, and prototypes to demonstrate research value.
- PhD in computer science, electrical engineering, or related field.
Research experience in machine learning, computer vision and driver behavioral analytics.
- Research experience in temporal modeling preferred.
- Experience in Deep Learning frameworks such as TensorFlow, Caffe or related tools preferred.
- Hands on experience with human monitoring devices such as eye tracking systems preferred.
- Experience in Robot Operating System (ROS) preferred.
Highly proficient in software engineering using C++ and Python.
- Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents.
- Strong publication record in the areas of computer vision, machine learning, and human-machine interaction.
Application Instructions: Please send an email to firstname.lastname@example.org with the following:
- Subject line including the job number you are applying for
- Recent CV,
- A cover letter explaining how your background matches the qualifications
Candidates must have the legal right to work in the U.S.A.