Research Scientist/Engineer - Department of Mechanical, Materials and Aerospace Engineering

The Department of Mechanical, Materials, and Aerospace Engineering (MAE) in the Benjamin M. Statler College of Engineering and Mineral Resources at West Virginia University (WVU) invites applications for a Research Scientist/Engineer in the general areas of Flight Dynamics, System Identification and Machine Learning.

Responsibilities will include but are not limited to the following: 1) conducting research on unsteady flight dynamics, system identification and algorithm development; 2) attending research conferences and reading of scientific literature to keep abreast of technological advances and latest research findings; 3) identifying public, private, or governmental research sponsors and assisting with the acquisition of funding from such sources; 4) searching scientific literature to select and adapt methods or procedures that are most appropriate for specific research goals; 5) overseeing research facilities and personnel; 6) writing and presenting research/study status reports for review and use by the Principal Investigator; 7) preparing results of experimental findings for presentation to colleagues and sponsors at professional/technical conferences; and/or, for publication in scientific journals, as directed.

West Virginia University is the State's comprehensive Land Grant University with an enrollment of about 29,000 students and a R1 Carnegie Classification. Morgantown and its vicinity have a diverse population of about 62,000 residents and is ranked highly among the most livable small cities in the country. The community lies within a high technology corridor that also includes several federal research facilities, as well as industries active in shale gas operations. The city is readily accessible and within driving distance from Pittsburgh, PA and Washington, DC. For more information on WVU and Morgantown, see http://www.wvu.edu and http://www.morgantownwv.gov.

An advanced degree in Aerospace Engineering, Computer Science, Electrical Engineering, Physics, Data Science, or related discipline is required. Experience with flight aerodynamic and performance analysis, Machine Learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn), and computational fluid dynamics is highly desirable.

To apply for this position, visit https://careers.wvu.edu/career-opportunities. Applicants must submit a cover letter, curriculum vitae, and contact information for three professional references. Only candidates who submit complete documentation will be considered in the review process. For questions or additional information, contact Dr. Piyush Mehta, 612-481-7542, email: piyush.mehta@mail.wvu.edu. You may also visit the MAE website at https://mmae.statler.wvu.edu/

West Virginia University is a place of purpose and community. We take pride in our profound impact on the state of West Virginia and are committed to the personal and professional growth of our employees.

From the groundbreaking R1 research at our flagship campus in Morgantown to the career-oriented programs at WVU Potomac State in Keyser, and the technology-intensive programs at WVU Tech in Beckley, the contributions of WVU employees resonate across the state, touching lives and shaping futures.

At WVU, you will discover a supportive community that champions work-life balance and fosters a collaborative atmosphere. Our core values - service, curiosity, respect, accountability and appreciation - unite us as Mountaineers.

We are dedicated to creating an inclusive and engaging working environment and actively seek candidates who bring diverse ideas, approaches and experiences.

Join us at West Virginia University, where your work will make a lasting impact. To learn more about WVU, visit wvu.edu.

West Virginia University is proud to be an Equal Opportunity Employer and is the recipient of an NSF ADVANCE award for gender equity. We value diversity among our faculty, staff and students and invite applications from all qualified applicants regardless of race, ethnicity, color, religion, gender identity, sexual orientation, age, nationality, genetics, disability, or Veteran status.