Dreyfus Foundation Machine Learning in the Chemical Sciences and Engineering
Camille & Henry Dreyfus Foundation (Machine Learning in the Chemical Sciences and Engineering)
- Proposal: 04/02/2020
- Amount: Indirect costs and institutional overhead are not allowed.
The Dreyfus program for Machine Learning in the Chemical Sciences and Engineering provides funding for innovative projects in any area of Machine Learning (ML) consistent with the Foundation’s broad objective to advance the chemical sciences and engineering. The Foundation anticipates that these projects will contribute new fundamental chemical understanding, insight, and innovation in the field.
The Foundation encourages proposals to significantly stimulate and accelerate the development of the use of ML and other related aspects of data science to the Chemical Sciences and Engineering. Below are some examples 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 ML 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 ML
Note that proposals are not restricted to the areas described above.
Funding: The amount requested is determined by the applicant. Partial contributions to larger scale efforts will be considered. Charges associated with indirect costs or institutional overhead are not allowed.
Eligibility & Submission Requirements
Principal investigators are limited to one proposal annually.
Procedural questions may be directed to the Foundation office by telephone at 212-753-1760 or e-mail at firstname.lastname@example.org