Center for Intelligent InfrastructureApplication Deadline
Posted Until FilledFull Time/Part Time
Full-Time Job Description
Post docs will be sought in one or more of the following areas to support infrastructure inspection and maintenance: (1) artificial intelligence and machine learning, (2) robotics with aerial manipulation, and (3) augmented reality, virtual reality, and digital twin.Artificial Intelligence and Machine Learning
. The successful candidate will help develop a deep learning defect detection approach for utility-scale solar farms from drone-based thermal and hyperspectral imaging. This study is to address the challenges of data collection and data processing that existing drone-enabled thermal imagining inspection techniques face with. In addition to the infrared and hyperspectral cameras, a Global Positioning System (GPS)/Inertial Measurement Unit (IMU) device will be mounted on a drone for automatic geo-referencing of the defects on solar panels. The hyperspectral camera is used instead of a RBG camera because the sunlight reflection in hyperspectral imaging will be beneficial to the data collection in daytime, which can significantly reduce the difficulty of data collection task associated with RGB imaging and improve the data quality. In the data process task, an online user-friendly platform integrated with deep learning models will be developed for automatic image analysis and localization.Robotics with Aerial Manipulation
. The successful candidate will help develop a new robotic platform to support inspection and/or maintenance with active robotic arms. Robot actions include the placement of sensors on elevated structures to quantify defects/damage, the robotic interaction with elevated structures for active nondestructive evaluation, and the local maintenance of bridges such as crack sealing and debris cleaning. Robots can be in the form of unmanned aerial vehicles and structural crawlers or their combination. System integration and prototyping expertise and hands-on experience are of great interest.Augmented Reality, Virtual Reality, and Digital Twin
. The successful candidate will help develop and set up a new visual inspection laboratory with augmented learning and train a cohort of 10 robot operators for bridge inspection each class. In addition, the candidate will conduct innovative research to advance augmented/virtual reality technologies for effective infrastructure inspection and hazard mitigation training, and to combine augmented/virtual reality with computational modeling to develop a digital twin of an infrastructure environment with two-way digital threads between digital and physical worlds. The new lab will be equipped with an augmented/virtual reality environment for three levels of robotic training. At the first level, both a robot and a bridge will be simulated using 3D models and visualization tools in a controllable (virtual) environment. At the second level, a robot prototype and a virtual bridge will be simulated in a hybrid real and virtual world. At the third level, both a robot and a bridge will be prototyped for the ultimate training of pilots/inspectors in various real-world scenarios.
Review of applications will begin as they receive and will continue until the position is filled. Interested candidates should electronically submit an application package consisting ofa cover letter, a current curriculum vitae, a statement of research interests and goals, and complete contact information for three references
to the Missouri University of Science and Technology's Human Resource Office using the following link:https://hr.mst.edu/careers/. All submitted application materials must have the position reference number 00038067 in order to be processed. Acceptable electronic formats that can be used for email attachments include PDF and Word; hardcopy application materials will not be accepted.
Ph.D. in civil engineering, electrical engineering, mechanical engineering, or computer science
The final candidate is required to provide copies of official transcript(s) for any college degree(s) listed in application materials submitted. Copies of transcript(s) should be provided prior to the start of employment. In addition, the final candidate may be required to verify other credentials listed in application materials.
Failure to provide official transcript(s) or other required verification may result in the withdrawal of the job offer.
All job offers are contingent upon successful completion of a criminal background check.
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