Job Title:

Job Summary:

Full Job Description:

Responsibilities:

Research

• Conduct research on advanced artificial intelligence techniques for the accurate detection, classification, and tracking of VRUs using video and point cloud data. 

• Develop innovative sensor calibration and fusion techniques to improve the precision and reliability of class perception mechanisms for VRUs.

•  Perform real-time motion analysis, conflict assessment, and risk assessment based on the status and predicted trajectory of VRUs.

•  Integrate Graph Neural Network (GNN) architectures for modeling relational dependencies among VRUs and improving trajectory prediction accuracy.

Development

• Collaborate with interdisciplinary teams to design and implement algorithms and models for VRU detection and safety assessment.

• Utilize deep learning methodologies for video and point cloud object recognition and detection.

• Implement and optimize GNN architectures for dynamic graph modeling and trajectory prediction.

Qualifications

• Ph.D. or equivalent experience in computer science, engineering, or related field.

• Strong publication record demonstrating expertise in deep learning techniques related to video and point cloud object recognition/detection. 

• Familiarity with main deep learning packages such as TensorFlow, PyTorch, or Keras.

• Proficiency in programming languages, particularly Python

• Familiarity with Graph Neural Networks (GNNs).

• Experience with sensor calibration, fusion techniques, and real-time motion analysis preferred.

• Ability to work collaboratively in interdisciplinary teams. 

• Excellent analytical and problem-solving skills.

Submission Instructions:

Application Deadline: May 15, 2024

Please submit the following application materials:
1. Research statement (not more than 3 pages)
2. Writing samples
3. CV or résumé
4. Contact information for 3 potential recommenders

Applications will be accepted on a rolling basis, but early submission is encouraged. The appointment is tentatively expected to run for 1 calendar year, with the possibility of extension for an additional 6 months.
 

Full-Time/Part-Time:

Pay Rate:

Salary Range :