Research Associate in Mechanical Engineering – Condition Monitoring and Computer Vision

UMass Lowell-posted 1 day ago
Full-time • Entry Level
Lowell, MA
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The successful "Research Associate in Mechanical Engineering - Condition Monitoring and Computer Vision" will conduct analytical and experimental research in the areas of Nondestructive evaluation and Condition Monitoring with an emphasis on the development of computer vision and machine learning-enhanced techniques for damage detection, data acquisition, and system monitoring for energy systems (e.g., wind, solar, hydrogen). 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 the possibility of renewal based on productivity and performance and the availability of funding.

  • Conduct analytical and experimental research under the supervision of the Principal Investigator (PI). This specifically involves: 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. Conduct research related to differing environmental conditions and operations of the installed energy storage and power generation system. Develop a supervisory control and data acquisition (SCADA) system for monitoring and control of energy systems. 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.
  • Assist supervisor in writing scholarly articles and proposals for grant funding. The successful candidate will be expected to publish at least two articles per year in peer-reviewed scientific journals based on the research conducted. Papers and presentations in scientific conferences will also be required. Development of patentable technologies over the course of the project will also be encouraged. The successful candidate will be expected to initiate and assist in the formulation and writing of externally funded research proposals. This effort will include finding appropriate opportunities, finding collaborative partners, generating preliminary data, and proposal writing/submission. Assist in preparing programmatic reports and making presentations to the sponsor/funding agencies.
  • Attend Meetings related to the research projects. Conduct weekly meetings between PI, Co-PI, and other group members (e.g., other Post-docs, graduate students, undergraduate students). Disseminate knowledge by attending technical meetings and conferences nationally and internationally when required.
  • Supervise Undergraduate and Graduate Students: Meet weekly with each student to review their research project, progress, and papers and to develop a path forward. Provide mentorship or training to graduate and undergraduate students involved in the project.
  • Promote the University’s commitment to customer service.
  • Build effective partnerships with co-workers throughout the University.
  • Ensure optimum service to all internal and external partners in response to all requests for service and information.
  • Maintain an environment that is welcoming to persons of all backgrounds, nationalities, and roles.
  • Help with the general operation of the lab and Center for Energy Innovation
  • Help to perform other new related duties as assigned.
  • Education: MS or PhD in Mechanical Engineering, Industrial/Systems Engineering, Civil Engineering, Electrical Engineering, Computer Engineering/Science, Physics, Applied Physics, Chemistry, or related scientific degree.
  • Experience: Minimum three years of experience (including MS and/or PhD. research experience) in research related to structural health monitoring and image processing, data acquisition, signal processing, and experience in conducting analytical research, experimental planning and testing in laboratory environments.
  • Skills: Ability to work as a team player.
  • Outstanding technical report writing and communication skills.
  • Experience in the development of computer algorithms and models for monitoring and control of mechanical, electrical and energy systems and physical parameters, as well as a 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, such as digital image correlation, infrared thermography, LiDAR, ultrasonic imaging, or other relevant methods.
  • Publications in the field of structural health monitoring, nondestructive evaluation, and image/signal processing.
  • Experience in computer code/software development (e.g., MATLAB, Python, C/C++, or similar).
  • Proficiency with operation of computers, programming languages, and Microsoft Office Suite.
  • Excellent Communication skills: E-mail, verbal, written, oral presentations, highly responsive
  • Ability to work independently, with limited direction, as well as within a team environment.
  • Ability to mentor and inspire students with limited research experience.
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