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"Post Doctoral Fellow - Structures and Artificial Intelligence Lab - (494536)"

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Post Doctoral Fellow - Structures and Artificial Intelligence Lab - (494536)

Possesses, understands, and applies a comprehensive knowledge in area of specialization. Develops understanding and skills to allow for completion of assignments that cross fields of specialization. Develops leadership and management skills.

1. Receives/Reviews progress and evaluates results of experiments or projects under control or supervisory responsibility.

2. Recommends changes in research, testing or experimental procedures.

3. May be responsible for a single highly technical and complex piece of research equipment.

4. May review and evaluate the effectiveness of personnel.

5. May plan for and assign personnel to projects under control.

6. Operates with latitude for unreviewed action.

7. May receive general supervision conferring with higher levels only in unusual situations.

8. Performs other job-related duties as required.

We are seeking a Postdoctoral Fellow to join a collaborative, interdisciplinary team working at the intersection of computer vision, and 3D AI for the built environment. Our goal is to transform how physical environments and infrastructure are captured, analyzed, and monitored using advances in 3D vision, AI-driven detection, and multimodal sensor integration (RGB, RGB-D, LiDAR), and digital twins. The postdoctoral fellow reports to Dr. Vedhus Hoskere in the College of Engineering/Civil and Environmental Engineering who may also be contacted for questions regarding the position (vhoskere@uh.edu)

This role offers an opportunity to lead cutting-edge research with a stellar research team, while contributing to development efforts from algorithm design and testing, synthetic data generation, user interfaces, and model deployment. Initial appointments will be for one year with the possibility of yearly renewal subject to funding availability.

Key Responsibilities

  • Conduct and lead research in 3D computer vision, deep learning, and AI for digital twin generation, publish findings in top journals and venues. (33%)
  • Mentor and manage graduate and undergraduate student researchers while executing project deliverables (25%)
  • Curate multimodal real and synthetic datasets, including photogrammetry, LiDAR, and depth cameras, to build scalable analysis pipelines (10%)
  • Contribute to field data collection for validation of developed approaches (may involve occasional travel) (2%)
  • Contribute to software tools to deploy developed approaches (10%)
  • Contribute to other publications, grant proposals, and internal R&D efforts (10%)
  • Contribute to professional service activities (10%)

Minimum Qualifications

  • Ph.D. in Civil/Electrical/Mechanical Engineering, Computer Science, Data Science, or a related field
  • Demonstrated expertise and publication record in computer vision, machine learning, 3D scene understanding, or digital twins
  • Experience working with real-world and synthetic datasets and sensors (e.g., RGB, depth, LiDAR)
  • Proficiency in Python and frameworks such as PyTorch, OpenCV, or Open3D
  • US Citizenship or Permanent Residency required

Preferred Additional Qualifications

  • Background in photogrammetry, 3D graphics, or sensor fusion for structural modeling
  • Track record of publications in top venues and contributions to applied industrial/research projects
  • Proficiency in Python, C++, and javascript
  • Exposure to full-stack development (e.g., UI tools, cloud pipelines, DevOps) is a plus

MQ: Requires singular knowledge of a specialized advanced professional discipline or the highest level of general business knowledge, normally acquired through attainment of a directly job-related terminal degree or equivalent formal training in a recognized field of specialization that is directly related to the type of work being performed. No experience is required.

All positions at the University of Houston-System are security sensitive and will require a criminal history check.

The University of Houston System and its universities are Equal Opportunity Institutions. Everyone is encouraged to apply.

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