Scientific Machine Learning for Modeling and Simulations

Funding Agency:
Department of Energy

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in research applications to explore potentially high-impact approaches in the development and use of artificial intelligence and machine learning (AI/ML) for predictive scientific modeling and simulations.

Scientific machine learning is a core component of artificial intelligence and a computational technology that can be trained, with scientific data, to augment or automate human skills. Major research advances will be enabled by harnessing DOE investments in massive amounts of scientific data, software for predictive models and algorithms, high-performance computing (HPC) and networking platforms, and the national workforce. The crosscutting nature of machine learning and AI provides strong motivation for formulating a prioritized research agenda.

Scientific Machine Learning and Artificial Intelligence (Scientific AI/ML) will have broad use and transformative effects across the research communities supported by DOE. Accordingly, a 2019 Basic Research Needs workshop report identified six Priority Research Directions. The first three PRDs describe foundational research themes that are common to the development of Scientific AI/ML methods and correspond to the need for domain-awareness, interpretability, and robustness. The other three PRDs describe capability research themes and correspond to the three major use cases of massive scientific data analysis (PRD #4), machine learning-enhanced modeling and simulation (PRD #5), and intelligent automation and decision-support for complex systems (PRD #6).

The principal focus of this FOA is on Scientific AI/ML for modeling and simulations (PRD #5). Foundational research (PRDs #1, 2, and 3) will be needed for strengthening the mathematical and statistical basis in developing predictive AI/ML-based computational models and adaptive algorithms for scientific advances. Also, new techniques, software tools, and approaches will likely be needed to reap scientific benefits from the extreme heterogeneity of scientific computing technologies (e.g, processors, memory and interconnect systems, sensors) that are emerging.

Deadlines:

  • Required Letter of Intent Due Date: May 1, 2020
  • Application Due Date: May 29, 2020

Agency Website

Eligibility Requirements

All types of domestic applicants are eligible to apply, except Federally Funded Research and Development Center (FFRDC)8 Contractors, and nonprofit organizations described in section 501(c)(4) of the Internal Revenue Code of 1986 that engaged in lobbying activities after December 31, 1995.

Limitation on the Number of Pre-applications: An individual may participate in no more than two pre-applications. If the same individual is a project member on more than two preapplications, the most recently received pre-applications will be accepted and all other preapplications will be discouraged from the submission of an application.

Limitation on the Number of Applications: An individual may participate in no more than two applications. If the same individual is a project member on more than two applications, the most recently received applications that match a qualified pre-application (as described in Section IV B. below) will be accepted and all other applications may be declined without merit review.

Amount

$300,000

Amount Description

Awards will be made for $150,000 per year. DOE anticipates making awards with a project period of two years.

Funding Type

Grant

Eligibility

Faculty
Women and minorities encouraged

Category

Engineering and Physical Sciences

External Deadline

May 1, 2020