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UNIVERSITY OF MASSACHUSETTS DARTMOUTH

Assistant Professor

Mechanical Engineering Department

The University of Massachusetts Dartmouth invites applications for a tenure-track faculty position at the Assistant Professor level in the Department of Mechanical Engineering () beginning in September 2024. We are specifically looking for candidates with strength in smart manufacturing processes and system design, advanced materials and processing, applications of advanced statistical modeling and analytics and Artificial Intelligence (AI)/Machine Learning (ML) for design, operation, control, monitoring/diagnosis/prognostics, and decision making in manufacturing.

The University of Massachusetts Dartmouth (UMassD) is located in the beautiful ocean side community of Dartmouth, about an hour south of Boston, a half-hour east of Providence, and a half-hour west of Cape Cod. It offers a world-class education to more than 7,500 undergraduate and graduate students each year in nearly 60 undergraduate and 50 graduate (MS & PhD) programs offered by the College of Engineering, College of Nursing, Charlton College of Business, College of Arts and Sciences, College of Visual and Performing Arts, School of Law and School for Marine Science and Technology. UMassD has transformed the lives of more than 50,000 alumni and distinguishes itself as a vibrant, public research university dedicated to engaged learning and innovative research. UMassD is the only Massachusetts national research university south of Boston and serves as a catalyst for the development of marine science and technology industries along the south coast of Massachusetts.

The Department of Mechanical Engineering combines a tradition of excellence in undergraduate education with a strong research culture. The successful candidate will join a world-class research team with existing strengths in a wide array of interdisciplinary fields including fracture and mechanical behavior of composites, damage sensing and diagnostics, quality control, additive and nanomanufacturing, multiphase heat and mass transfer modeling, experimental fluid mechanics with fluid structure interaction, boundary layer visualization and 3D imaging, scientific computing, renewable energy with emphasis on the blue economy and energy storage materials. All the tenured and tenure-track faculty members are active in externally funded research grants and contracts, with funding from a variety of sources, most significantly NSF, ONR, NIH and DOE. We expect candidates to actively seek and foster meaningful collaborations with our esteemed faculty in fluid and thermal sciences, materials, robotics, and leverage the entire emphasis of the university on the blue economy.

Duties: The successful candidate will be expected to develop a nationally recognized, externally funded research program; teach and advise undergraduate and graduate (MS & PhD) students; contribute to university and professional service; foster interdisciplinary collaborations; and engage in college and university diversity, equity and inclusion initiatives.

Minimum Qualifications: Candidates must have earned bachelor's and doctorate degrees in Mechanical engineering or a closely related field at the time of appointment and demonstrate a strong commitment to teaching excellence and scholarly research as well as diversity, equity and inclusion.

Preferred Qualifications:

Strong candidates will have research experience in a mechanical engineering field and teaching experience in higher education. Postdoctoral research in an interdisciplinary setting is highly desirable. We are especially interested in receiving qualified applications from underrepresented minorities and women.

Candidates are required to have strong skills and research interests in one or more of the following areas: advanced manufacturing (system-level modeling and analysis, automation and process control; additive, nano- and bio-manufacturing; human-automation interaction and human-robot interaction; digital twins; advanced materials and processing; and the security of cyber-physical industrial systems), statistical modeling/analysis/computing, prognostic health management, big data fusion and machine learning with multi-physics simulation and heterogeneous data, and simulation in manufacturing systems. Candidates with strong research interests in advanced manufacturing systems and related areas, especially for manufacturing semiconductors, EVs, and rechargeable batteries, are encouraged to apply.

Application Process: Qualified applicants are invited to submit electronically a letter of interest, detailed curriculum vitae, concise statements on research plans, teaching philosophy, and diversity, and contact information for at least three professional references. Employment is contingent upon verification of background/credentials and work authorization.

Screening of complete applications will begin on December 15, 2023 and will continue until the position is filled.