MAPS: Machine Learning and Physical Sciences

National Science Foundation/UCI Graduate Training Program

The MAPS Graduate Training Program

MAPS is part of the National Science Foundation Research Traineeship (NRT) Program. MAPS has been funded by NSF for 5 years (2016-2021) to train and support graduate students working on interdisciplinary research at the interface of (1) machine learning/statistics, and (2) the physical sciences (particle physics, chemistry, earth sciences, astronomy), with an emphasis on team science. Advances over the past decade in sensor technology, storage capacity, computational power, and data analysis methodologies have ushered in a new era of data-driven science. To fully realize the benefits of massive scientific data sets requires training graduate students with skills in data science and team science.

The project will support at least 20 PhD students via research fellowships over the duration of the program with a comparable number of honorary fellows (both MS and PhD) also participating. These students will be from diverse backgrounds in machine learning, computational statistics, earth science, particle physics, synthetic chemistry, and team science. The program will involve a variety of activities for students, including monthly research meetings, opportunities to meet leading researchers, participation in an annual symposium, summer internship opportunities at leading research labs, and more. After graduation, students from this program will have both the technical and team-science skills to be leaders in the emerging field of data-driven science, and to participate in and lead interdisciplinary research teams at national laboratories, in academia, and in industry labs.

See also the NSF description of the program.