Proposal Deadline: April 2, 2020
The goal of this program is to further the understanding and applications of machine learning throughout the chemical sciences, thereby providing new opportunities.
“In view of the increasing attention to and expectations for the profound impacts that artificial intelligence and data science will have on physical science and engineering, the Dreyfus Foundation plans to make strategic investments in machine learning for the chemical sciences and engineering, both to advance the field in these areas, and to help position the chemical sciences field to best avail itself of the broad agency opportunities for research support that are emerging. We are enthusiastic about the potential for machine learning to produce useful fundamental and practical insights in chemical research.” -Richard N. Zare and Matthew V. Tirrell, Camille and Henry Dreyfus Foundation, Scientific Affairs Committee of the Board of Directors.
Below are some examples of areas this program may support:
- molecular synthesis, including mechanisms, techniques, and applications
- theory, computation, physical properties of molecules or materials
- rates and mechanisms of new chemical processes
- new or improved materials and materials applications
- postdoctoral support for collaborations that combine chemical science research with machine learning expertise
- collaborative sabbaticals, extended visits and meetings
- education, e.g., new courses, seminar series, MOOCs,…
- public libraries of chemistry and chemical engineering data for use in machine learning
Note that proposals are not restricted to the areas described above.
Additional details are available at the Foundation website.