NSF-IPAM Workshop Tackles Workforce Issues

Therefore, the mathematical community faces a significant workforce issue: we need to prepare mathematical sciences students for a variety of career paths, but many faculty do not have experience in BIG.  Internships provide a viable way for students to interact with mentors, gain work experiences, and engage with interesting mathematics problems while pursuing their Ph.D.s. These internships can be regular components of a Ph.D. program, or part of a summer work experience.

Internships were the focus of the NSF-IPAM Mathematical Sciences Internship Workshop held at the Institute for Pure and Applied Mathematics (IPAM) at the University of California, Los Angeles (UCLA) in September 2015. The workshop was organized by Russel Caflisch (UCLA), Alan Lee (Advanced Micro Devices), James L. Rosenberger (Penn State), and Rachel Levy (facilitator, Harvey Mudd College). The diverse group of participants brought perspectives from academic (college/university, public/private), business (large/small), and governmental institutions as well as many areas of the mathematical sciences.

Working groups focused on support, training, logistics, recruiting, and culture. The workshop aimed to accomplish the following: develop recommendations for infrastructure and programs to increase the number of internships targeting mathematical sciences students; open the internship pipeline to a diverse group of students; offer assistance with timing and logistics for undergraduates, graduate students, and postdocs in pure and applied mathematics; provide training to prepare mathematical sciences students for internships; and develop viable models of how internships best work for mathematical sciences students, postdocs, faculty, and personnel in BIG. 

To address the multi-faceted training needs of students, workshop groups recommended a distributed network internship initiative with national, regional, and local components.  

National level: Create a national network to increase internship information exchange, data collection, access, and opportunities:

• Design and implement a data-gathering project to develop the mathematical sciences internship landscape and provide baseline data for new initiatives
• Offer communication and coordination of best practices, training materials and opportunities, models for local programs, and media to aid regional and local outreach efforts  
• Build a national network of individuals, companies, government labs, academic institutions, math societies, and mathematical sciences institutes to exchange information and increase and advertise internship opportunities 

Regional level: Establish regional internship centers to build internship contacts and organize training opportunities:

• Build internship contacts and opportunities in the region
• Offer centralized training (that could be replicated locally), such as short courses in programming, soft skills, and data
• Hire internship development staff to serve as liaisons between local institutions and potential internship sites and to promote mathematical sciences internships in BIG by communicating how mathematical sciences students make contributions

Local academic level: Encourage and enable student participation in internships in mathematical sciences departments:

• Encourage students to pursue training and internships
• Disseminate information from national and regional organizations
• Identify the department chair, director of graduate study, or an interested faculty member to build local institutional mechanisms for internships  

To receive information on upcoming internship initiatives, please send your name, institution, and email address to bigmathnetwork@siam.org. The full NSF-IPAM Mathematical Sciences Internship Report is available on the IPAM website.

¹ www.ams.org/annual-survey

² http://fortune.com/2015/01/22/the-algorithmic-ceo/