Program Opportunities, Requirements, and Eligibility

Applications will open in Fall 2025.

Trainee Opportunities and Benefits

For each year they are funded, RAISE Fellows will receive a $34K stipend, and their tuition, fees, and benefits will be covered. MSc students will receive one year of funding, and PhD students will receive two years of funding.

RAISE Fellows will participate in at least one summer research internship with RAISE industry and government laboratory partners.

A series of workshops will be provided, focused on essential skills in communication, ethics, mentoring, and teamwork.

All RAISE Fellows will participate in a formal triad mentoring program, in which a senior RAISE Fellow, a junior RAISE Fellow, and an industry or government lab researcher, or faculty member will work together to share information and advice related to career advancement.

Course requirements

RAISE Fellows will take a core sequence of three classes:

1. Machine Learning (ECE 517), Introduction to Machine Learning (CS 529) or AI for All (OILS 584)
2. Ethics of AI in Autonomous Systems (Fall)
   CE 598-004, CS 591-001, ECE 595-004, GLNS 595-005, ME 561, OILS 593-002
3. Design of Human-Centered AI in Autonomous Systems (Spring)
   CE 598, CS 591, ECE 595, GLNS 595, ME 561, OILS 593

in addition to relevant coursework in their department. The first class provides a foundation in the basics of machine learning. The second and third courses form an interdisciplinary, two-course sequence that is co-taught by faculty in the School of Engineering and in the Organization, Information, and Learning Sciences department. The second class covers ethics as a type of problem solving that requires a design-based approach for devising solutions and specific strategies for inscribing ethics into design, such as articulating ethical considerations as specifications and stakeholder involvement. The third class is a project-based design class, in which students will devise possible solutions that aim to optimize technical, ethical, and other specifications (and be prompted to revise their models) to projects informed by our industry and government lab sponsors. The content features units on technical foundations and human implications of training bias, neural net fragility, and physics-informed neural nets, as well as principles of human factors in autonomous systems.

Eligibility

While all students with appropriate interests and backgrounds are encouraged to participate in the RAISE program, there are restrictions on eligibility for receiving a graduate stipend through a RAISE Fellowship. Eligibility does not ensure a Fellowship award.

Applicants to the RAISE Fellowship must:

• be US citizens, US nationals, or US permanent residents;
• be admitted to a MSc (Plan I) or PhD degree program in one of the RAISE-affiliated departments (CE, CS, ECE, ME, OILS);
• begin their graduate degree in the year coinciding with or the year before the fall semester start of RAISE.

Please note that students pursuing a non-thesis (Plan III) MSc degree are ineligible for a RAISE Fellowship.