Science Lab

AIMEMS NRT Project Overview

Motivation : Unique interdisciplinary engineering school configuration; integration of AI/ML with molecular engineering accelerates scientific discovery and technological innovation; world-class facilities at Argonne to enrich graduate student training.


Disciplines/Fields Engaged : Molecular Engineering, Computer Science, Social Science.


AIMEMS Trainees : 20 NRT trainees with stipend (15 PhD, 5MS), 25 NRT trainees without stipend (15 PhD, 10 MS), 100 other STEM graduate students (i.e., non-trainee MS and PhD students).


Example Research Project : AI-enabled design and manufacturing of water quality sensors involving identification of sensitive, and specific probes for particular analytes using AI-directed high-throughput virtual screening.


Education/Training Models : New courses with course modules on unique Argonne user facilities (e.g., APS-U, Aurora supercomputer, and MERF); co-advising of graduate students by a UChicago faculty, an Argonne scientist, and an industry mentor; collaborative teams of three students from different disciplines will work together on joint projects.


Innovative PD Activities : Leveraging programs across the campus to train students on communication, teaching and mentoring, leadership and management, and career exploration preparedness

Informed by recent National Academies Reports and customer surveys, the proposed AIMEMS NRT program aims to train University of Chicago (UChicago) graduate students on artificial intelligence (AI)/machine learning (ML) and AI-enabled molecular engineering of materials and systems for sustainability.  The AIMEMS NRT will train 20 NRT trainees with stipend (15 PhD, 5 MS) and 25 NRT trainees without stipend (15 PhD, 10 MS), producing a total of 45 NRT trainees. In addition, 100 other graduate students will benefit from NRT project components over the 5-year period.  The program is empowered through strategic partnership with Argonne National Laboratory (Argonne) by leveraging Argonne’s world-class expertise and facilities in materials characterization (e.g., Advanced Photon Sources – Upgrade or APS-U), supercomputing (e.g., Aurora supercomputer), and materials engineering research facility (MERF).  New courses in AI/ML for molecular engineering, advanced materials characterization, supercomputing, and scalable manufacturing with course modules tied to specific Argonne facilities will be developed.  Students will have opportunities to take these new courses as well as existing UChicago courses to receive graduate degrees or a minor degree/certificate in computational molecular engineering. Students’ professional skills will be trained through seminars, mini-courses, workshops and annual retreats. Research connections will be established through various cutting-edge, team-based, convergent research projects.  The integration of AI/ML in these research projects will accelerate scientific discovery and technological innovation.  Graduate students will be co-advised by a team consisting of a UChicago faculty, an Argonne scientist, and an industrial advisor.  The proposed NRT program has the potential to serve as a national model for training next-generation AI-empowered graduate student leaders through strategic, inclusive university-national laboratory-industry partnerships.