About the program

The NRT program offers unique graduate traineeship experience to M.S. and Ph.D. students pursuing research on grand challenge problems interfacing materials science, data analytics, and machine learning (ML). The program harnesses the strength in polymer materials science at The University of Akron (UA), the important progress in data analytics and machine learning tools, and the intangible values of nonacademic internship opportunities at federal and industrial laboratories to design a unique interdisciplinary graduate traineeship that has the potential to impact a total of 40 graduate trainees (20 NRT-funded, 20 non-funded cohort) in the five-year funding period. The grand total number of students expected to benefit from this program is 80-100 Ph.D. and 50-60 M.S. students.

The trainees will have strong participation from underrepresented minorities in science and engineering. The proposed research is rooted on four main topics with societal impacts: (1) advances in additive manufacturing of polymeric composite materials; (2) discovery of new solid-state electrolytes to enhance battery performance; (3) design of new sustainable and recyclable polymeric materials; and (4) development of scalable data management platforms and tuning of ML tools for materials research. This interdisciplinary traineeship program builds on collaborative work of 6 core UA investigators with expertise in polymer synthesis and engineering, molecular dynamics modeling and machine learning, and data sciences and management. The trainees will acquire communication skills, teamwork habits, interdisciplinary knowledge, and international exposure from several interdisciplinary elements, such as lab rotations, new “ZIPS: Engineered for Success” workshop series and “Machine Learning and Data Science in Materials Research“ seminar series at UA, internships at government laboratories, participating industries, and international research universities. The NRT program will be assessed by the lead evaluator using a mixed methods evaluation design. UA commits to the sustainability of the proposed graduate education model beyond the 5 years funding period through strong institutional support and close long-term partnership with external collaborators.

Benefits to Students

The proposed work develops an interdisciplinary training program for the next-generation engineering and scientific workforce to lead integration of materials and data science research, impacting an estimated 40 NRT trainees in a five-year grant period and a similar number of trainees every five years. The trainees will receive a Data Science Engineering graduate certificate, while enrolled in UA’s M.S. or Ph.D. programs. The 40 NRT trainees in proposed funding period and future trainees will become strong proponents of ML and digitalization tools in materials research and acquire skills to work in none academic settings through internships at federal and industrial laboratories. This work will improve national security and enhance technological advancement for human welfare and clean energy. This program aims to improve the recruiting, retention, and mentoring of under-represented minorities and female engineers and scientists. The trainees will participate in outreach and mentoring activities of high school and 2-years community college students.

Computational Data Science, Certificate

Course information in the Bulletin of Classes