The Department of Energy (DOE) has announced a funding opportunity (NOFO DE-FOA-0003458) to support research and development in applying Artificial Intelligence (AI) and Machine Learning (ML) to nuclear science and technology. The focus is on autonomous optimization and control of accelerators and detectors used in nuclear physics, as well as enhancing nuclear physics computations. The program aims to use AI/ML tools to increase efficiency, accelerate discoveries, and solve complex challenges related to accelerators, instrumentation, and data analysis in nuclear physics.

Projects should address the following research areas:
- Efficient extraction of critical data from complex datasets generated by nuclear physics experiments.
- Development of digital twins for future colliders to optimize design and operation.
- AI-driven autonomous control of large nuclear facilities and instrumentation.
- Enhanced operations of accelerators and instruments to increase uptime and discovery potential.
- AI techniques to expedite data reduction for large experimental datasets.
- Software development to enable data-driven discoveries in nuclear physics.

Applicants can submit proposals either as new projects or as renewals. Collaboration across multiple institutions is allowed, but only one application is permitted per consortium. The DOE expects to distribute up to $22 million in funding across 10-15 awards, with individual projects ranging from $200,000 to $3.5 million over a project period of two years.

Eligibility extends to domestic institutions, including DOE National Laboratories and for-profit organizations. However, non-DOE/NNSA Federally Funded Research and Development Centers (FFRDCs) and other federal agencies are excluded from applying directly but may participate as subrecipients.

Key dates include a Letter of Intent (LOI) deadline of November 14, 2024, with full applications due by January 14, 2025.