Job Description

Are you ready to shape the future of urban mobility and make roads safer for vulnerable road users (VRUs)? At the University of San Francisco's Data Institute, we're embarking on a groundbreaking project: "Advanced Artificial Intelligence Research for Equitable Safety of Vulnerable Road Users." This initiative harnesses cutting-edge AI, real-time sensing technologies, and advanced algorithms to enhance traffic safety at intersections—because every road user deserves to get home safely.

This is your opportunity to apply your expertise in artificial intelligence and make an impact that extends far beyond research. Are you ready to lead the way?

Your Role

As a Postdoctoral Research Fellow, you’ll take on a pivotal role in developing cutting-edge AI techniques to improve VRU safety. From innovative sensor calibration to real-time trajectory prediction, your work will set new standards for equitable urban mobility.

What You’ll Do

Research:

• Pioneer advanced AI techniques to detect, classify, and track VRUs using video and point cloud data.
• Design innovative sensor calibration and fusion techniques to enhance the precision of VRU detection systems.
• Conduct real-time motion, conflict, and risk assessments based on VRU trajectories.
• Integrate Graph Neural Networks (GNNs) to model relational dependencies and boost trajectory prediction accuracy.

Development:

• Collaborate with interdisciplinary teams to develop and implement state-of-the-art algorithms for VRU detection and safety assessment.
• Apply deep learning methodologies to video and point cloud object recognition and detection.
• Optimize GNN architectures for dynamic graph modeling and trajectory forecasting.

What You Bring

• Ph.D. or equivalent experience in computer science, engineering, or a related field.
• A proven track record of publications in deep learning for video and point cloud object recognition/detection.
• Proficiency in TensorFlow, PyTorch, or Keras, and strong programming skills in Python.
• Experience with Graph Neural Networks (GNNs) and sensor calibration techniques (preferred).
• Strong analytical and problem-solving skills, with the ability to work collaboratively across disciplines.

Why Join Us?

• Innovative Impact: Be at the forefront of AI research while contributing to real-world safety solutions.
• Collaborative Environment: Work with an interdisciplinary team of experts passionate about equitable technology.
• Location Advantage: Immerse yourself in the dynamic, innovative energy of San Francisco—a global tech hub.
• Career Development: Gain unparalleled experience in advanced AI applications for social good.

Details at a Glance

• Duration: 1 year (possibility of a 6-month extension)
• Compensation: $81,120 annualized salary
• Location: University of San Francisco
• Application Deadline: May 15, 2024 (rolling applications; early submissions encouraged)

How to Apply

Submit the following materials:

1. A research statement (up to 3 pages)
2. Writing samples
3. Your CV or resume
4. Contact information for 3 recommenders