With the rapid development of information technologies, the applications of data science has dramatically changed various aspects of our society and economy. In responding to this emerging trend, the Texas A&M Institute of Data Science (TAMIDS) was established to pursue new approaches to data science research, education, operations and partnership at Texas A&M University.
Among all the objectives of TAMIDS, the education of the new generation of researchers that combine their disciplinary competences with data science expertise is of paramount importance. Through collaboration with A&M colleges, research agencies, and industrial partners, we are proud to start the TAMIDS Data Science Trainee Program that breaks college boundaries to bring together the expertise and skills from science, engineering, operations, business, health, education, etc. to solve challenging problems while preparing our students for their future career success.
We identify three roles – Project Leader, Trainee, and Consultant – in which people can be involved in the program with TAMIDS.
Propose Data Science projects by submission here; the proposals are posted online
Select and supervise one or more interested trainees to participate in the project
Help trainee to acquire domain knowledge needed to conduct the project
TAMU Role: faculty, research staff, post-doc or operations staff.
Register to participate in the program here and indicate their interest in specific project proposals
Participate in proposed project(s)
Attend TAMIDS and HPRC training events on Data Science and computing if needed
Learn background domain knowledge needed to conduct their project(s)
TAMU Role: undergraduate or graduate students
Assist Project Leaders with development of project proposals and trainee selection if requested
Provide trainee mentorship, project consultancy, and helps with evaluation
Consultants can register here
TAMU Role: faculty, research staff, post-doc, operations staff or graduate students
TAMIDS will support and sustain the Data Science Traineeship Program by (1) managing the program organization; (2) assisting in matching leaders, projects and trainees; (3) organizing Data Science workshops and training programs; (4) helping with project computing and storage resources, and (5) helping develop Data Science courses and curriculum with domain emphases.
We would like to invite A&M faculty, researchers, staff, and students to join this program to promote research, education, service, operations, and outreach in Data Science across Texas A&M. With your involvement and contribution, we will build a vibrant research and education environment for data science at Texas A&M.