Dreyfus Program for Machine Learning in the Chemical Sciences and Engineering – Awards vary – due Apr 7, 2022

Science, Technology, Engineering, and Mathematics (STEM) Program – Awards vary – Due Mar 30, 2022
December 14, 2021
E-Teams Grant Program – up to $25,000 – Due May 5 annually
December 17, 2021

Sponsored by Camille and Henry Dreyfus Foundation

Eligibility:            Public, Private

Award(s):           Awards vary.

Deadline(s):       Applications are due April 7, 2022.

Focus:   Engineering, Library/Media, Professional Development, Technology Equipment/Devices

Grade Level(s):  Higher Ed

Content Area(s):             Science

State(s):              National

Description:       The Camille and Henry Dreyfus Foundation awards Machine Learning (ML) in the Chemical Sciences and Engineering Grants to US academic institutions granting bachelor’s or higher degrees in the chemical sciences. 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. The foundation anticipates that funded projects will contribute new fundamental chemical insight and innovation in the field.

Examples of project concepts that may be supported include, but are not limited to, the following:

• Molecular synthesis, including mechanisms, techniques, and applications.

• Theory, computation, and physical properties of molecules and materials.

• Rates and mechanisms of new chemical processes.

• Postdoctoral support for collaborations that combine chemical science research with ML expertise.

• Collaborative sabbaticals, extended visits, and meetings.

• Educational activities including, but not limited to, new courses, seminar series, and MOOCs.

• Public libraries of chemistry and chemical engineering data for use in ML.

Contact:              The Camille and Henry Dreyfus Foundation

555 Madison Ave. 20th Fl.

New York, NY 10022-3301

Phone: 212.753.1760

Email: [email protected] (To submit applications)

Website:             https://www.dreyfus.org/machine-learning-in-the-chemical-sciences-and-engineering/