Jennifer Cutler, Assistant Director for Industry Engagement
Jennifer Cutler leads the TAMIDS Industry Affiliates program to build partnerships with academia, industry, non-profits, and National Labs. Her work includes workforce development and continuing education, enhancing student engagement, faculty research, and professional education. Jennifer coordinates with internal stakeholders, oversees industry outreach for the Data Science Capstone, and develops strategies to engage industry and national labs in TAMIDS research activities. If you have questions about the Industry Affiliates program, you can email Jennifer at jenniferjoe@tamu.edu.
Industry Affiliate Program
The TAMIDS Industry Affiliate Program connects member organizations with Texas A&M students who will form the next generation of leaders and innovators in Data Science, Artificial Intelligence, and Machine Learning. Industry Affiliates build on the TAMIDS network to strengthen their recruiting programs through Student Engagement, Recruitment Logistics, Brand Recognition, and R&D Engagement.
Named PH.D. Student Researcher or PostDoc Fellow
Make a lasting impact on Data Science through your company’s named researcher support.
Professional Training
The Texas A&M Institute of Data Science (TAMIDS) workshop on Data Science Foundations and Computational Practice is a week-long intensive workshop that equips participants with diverse skills to enable their professional practice of data science.
Capstone
Data Science Capstone projects run within the academic setting of the Master of Science in Data Science and other Graduate programs. The aim of the Data Science Capstone is to complement students’ knowledge of Data Science methods and technologies through the practice of its application to research problems in Data Science domains.
Faculty Experts: Research Affiliates
TAMIDS Research Affiliates are Texas A&M’s Data Science experts, with over 200 members drawn from 32 Texas A&M Colleges, Agencies, and other major organizational units. Research affiliates include Texas A&M faculty, researchers, staff, and professionals, whose roles and interests include Data Science.