POST Doctoral FELLOW - Electrical and Computer Engineering

Job Description

The project focuses on development of non‑contact AI‑based methods for analysis of human mobility and early detection of knee osteoarthritis (OA) using LiDAR point‑cloud sensing and machine learning. The effort includes dataset collection, AI model development for 3D pose estimation, extraction of biomechanical markers, and KOOS score estimation.

• Develop AI and machine‑learning models for LiDAR‑based human pose estimation.
• Develop algorithms for biomechanical marker extraction and KOOS score prediction.
• Support data collection and experimental validation.
• Publish research results in journals and conferences.
• Submit proposals for external funding.
• Recruit and supervise undergraduate and graduate students.

• Ph.D. in Computer Engineering, Electrical Engineering, or related field.
• Strong background in machine learning and AI.
• Experience with Python and deep learning frameworks such as PyTorch or Tensor Flow.
• Experience with computer vision, 3D sensing, or point‑cloud processing.
• Strong publication and communication skills.

• Experience with LiDAR sensing or motion analysis.
• Experience with pose estimation or biomechanical modeling.
• Familiarity with regression and multimodal data analysis.
• Experience with experimental data collection and evaluation.

This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, and educational fee discounts for all four UM System campuses. For additional information on University benefits, please visit the Faculty & Staff Benefits website at https://(Use the "Apply for this Job" box below)..

The University of Missouri is an Equal Opportunity Employer.

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