Enriched Doctoral Training in the Mathematical Sciences

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Presentation transcript:

Enriched Doctoral Training in the Mathematical Sciences Division of Mathematical Sciences

Some History of Workforce Program Postdoc | Graduate |Undergrad Vertical Integration of Research and Education in the Mathematical Sciences (VIGRE) (1998-2008) Research Areas

Research Training Group Mentoring Through Critical Transition Points Some History of Workforce Program Research Training Group (RTG 2004-) Postdoc Graduate Undergrad Mentoring Through Critical Transition Points (MCPT 2004-2013) Research Areas

Proactive Recruitment in Introductory Science and Mathematics (PRISM) Some History of Workforce Program Postdoc Graduate Undergrad Computational Science Training for Undergraduates in the Mathematical Sciences  (CSUMS) Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences  (UBM) Proactive Recruitment in Introductory Science and Mathematics  (PRISM) Research Areas

Enriched Doctoral Training in the Mathematical Sciences-Logic Model INPUTS PhD granting departments PhD students EDT grant money External partners (BIG) Other units in university Faculty OUTPUTS New training modules Internships Summer schools New Partnerships SHORT TERM OUTCOMES Doctoral students learn to recognize mathematical challenges coming from other disciplines and non-academic areas PhD graduates have the skills to apply advanced math and stat techniques to solve these problems LONG TERM OUTCOMES PhD graduates are well prepared for jobs in BIG PhD graduates are successful at obtaining jobs in BIG PhD graduates who go on to academic careers can serve as bridges PhD graduates who go on to academic careers can advise their students on large range of options Mathematical sciences departments have enhanced ties to other departments and to BIG IMPACT Advanced mathematical techniques exploited more widely to solve problems in many fields and sectors Advances in mathematical sciences, inspired by other fields, are brought about by trainees who have thorough understanding of both mathematics and domain space

Research Training Group Current DMS Workforce Program Mathematical Sciences Postdoctoral Research Fellowships (MSPRF) Research Training Group (RTG 2004-) Postdoc Graduate Undergrad Enriched Doctoral Training (EDT) Research Experiences for Undergraduates (REU Sites) Research Areas

The Goals of the EDT program Enhance U.S. doctoral training in the mathematical sciences to move beyond the paradigm of training in a single, tightly-focused topical area to include a broad range of graduate research experiences Prepare mathematical sciences doctoral students for a wide range of career paths

The first competition in 2015 resulted in two awards NSF award #1514808 to UT Dallas. Students spend two semesters in their second year working in teams on an interdisciplinary research project posed by an external partner, followed by summer internship. NSF award #1514606 to Princeton University. Students will work collaboratively with partners at several European policy centers on mathematical methods to solve problems related to water.

The 2nd competition in 2016 resulted in 4 awards. NSF award #1551069 to SUNY at Buffalo EDGE@UB year long supplementary training, summer internship, preceded by appropriate training NSF award #1551205 to U Minnesota Provides training over 6 weeks in a boot camp for domestic students across US. Soft skills, coding and industrial project.

The third and fourth are collaborative: FRAMEWORK. NSF awards #1551236 /1551299 to University of Wyoming & Colorado School of Mines. Students participate in video curriculum, sharing resources across campuses. One or two summers off site internships. Increase pool of minority students by target to CC students of mathematics options. Soft skills training on campus.

On the Horizon Mathematical Sciences Graduate Internships -through the Oak Ridge Institute for Science and Education (ORISE) The internships are aimed at students who are interested in understanding the application of advanced mathematical and statistical techniques to "real world" problems, regardless of whether they plan to pursue an academic or nonacademic career

Thank You!