NRT Training Philosophy
The NRT MIDAS trainees will build a strong grounding through core courses from their degree-program and receive with their NRT cross-training in secondary disciplines through elective coursework and interdisciplinary NRT-MIDAS courses. Mentoring from two academic co-advisors with expertise in different disciplines – high performance computing (HPC), data science (DS) and polymers & soft materials (MAT) – and regular interactions with researchers in industry and national lab will further solidify the interdisciplinary practical training. This technical training will be blended with professional skills development in ethics, inclusion, collaboration, team-science, adaptive communication, and interpersonal negotiation in every training element to ensure trainees from the different disciplines supporting HPC, DS, and MAT can overcome barriers involving discipline-specific communication and cultural differences. As a result of this NRT training, these trainees will serve as cross-functional connections between the MAT, HPC and DS disciplines pushing polymer informatics research forward with their gained knowledge of Materials Innovation, Discovery, and AnalyticS, or their ‘MIDAS’ touch.
NRT trainees and faculty advisors will participate in weekly community hour during the winter, fall, and spring semesters. This community hour will be open not only to the NRT trainees, NRT program coordinator, NRT core-team faculty members, primary or secondary doctoral thesis advisors of the trainees, but also to anyone (partner mentors, other UD and DSU graduate students, and postdocs) interested in participating in the community hour events.
These courses include the trainee’s core program courses, NRT specific courses, and elective courses.
The NRT trainee timelines fit in well with the trainees’ own graduate programs’ timeline and requirements (e.g., qualifying exams, number of core and elective classes) and keep the time to graduation for a successful NRT trainee on par with their peer non-NRT counterparts.