General Summary of Position:

One post-doctoral research associate position is available in the Department of Mechanical and Industrial Engineering at the University of Massachusetts Lowell. The position is under the direct supervision of Dr. Alessandro Sabato (Alessandro_Sabato@uml.edu). The successful applicant will conduct analytical and experimental research in the areas of nondestructive evaluation (NDE) with an emphasis on the development of computer vision and machine learning-enhanced techniques for damage detection in wind turbine blades.

The successful candidate will also assist in writing scholarly articles and research proposals, help to manage and educate graduate or undergraduate students, and assist in the successful operation of the laboratories and facilities.

The initial appointment will be for 1 year with a possibility of renewal based on productivity and performance and the availability of funding.

The project will involve conducting analytical and experimental research under the supervision of the Principal Investigator (PI). In particular:

• Acquire data of targeted structures using unmanned aerial vehicles embedding different sensors such as RGB, RGB_D, and infrared cameras, LiDAR scanners, etc.
• Develop appropriate image processing algorithms and approaches to analyze the collected datasets.
• Develop appropriate machine learning algorithms and models to automate the detection of damage in the collected datasets.
• Ensuring all project-related activities are conducted on time and to the highest standard.
• Prepare status reports and deliverables in collaboration with and under the direction of the PI.
• Serve as a liaison between PI and collaborating research partners.

Minimum Qualifications (Required):

• The successful candidate must have a Ph.D. degree in Mechanical, Electrical, Computer, Civil Engineering, or a closely related field by the start date of the appointment
• Minimum five years of experience (including MS and PhD. research experience) in research related to structural health monitoring and image processing
• Ability to work as a team player
• Outstanding technical report writing and communication skills
• Experience in the development of computer vision and machine learning algorithms and models for structural health monitoring/nondestructive evaluation.
• Knowledge of image segmentation, detection, classification, and automated detection techniques
• Familiarity with nondestructive evaluation techniques for the detection of geometry and damage in wind turbine blades, such as digital image correlation, infrared thermography, LiDAR, ultrasonic imaging, or other relevant methods.

Special Instructions to Applicants:

Only current UML Employees within the Grants & Contracts (MTA/GRACE) bargaining unit will be considered during the first 10 business days of the posting. All other candidates will be considered after that period.

Initial review of applications will begin immediately and continue until the position is filled. However, the position may close when an adequate number of qualified applications is received.

This position is contingent upon funding. The initial appointment will be for one year with a possibility of renewal based on productivity, successful performance and the availability of funding.

Please include a resume, cover letter, research statement (discussing how their relevant expertise in computer vision and machine learning), and a sample publication with your application. Names and contact information of three references will be required during the application process.