PhD Teaching Fellows

Each summer, i3 welcomes four PhD students to the University of Texas at Austin to participate in Introductory Institute as paid PhD Teaching Fellows. Fellows are responsible for developing and co-teaching either the Research Design or Computational Thinking & Tools Module.

The timeline for 2022 Teaching Fellowships is as follows:

  • March 1, 2023: Applications due
  • Mid-March, 2023: Decisions announced
  • Late March – June 2023: Fellows work remotely with i3 Leadership to iteratively develop modules
  • June 22, 2023: Fellows arrive at i3
  • June 26, 2023 – July 7, 2023: Fellows teach their two-week modules

Job Duties

Inside the classroom, PhD Teaching Fellows are responsible for teaching their respective module content 1.25 hours per day for 10 days across a 2 week period. Additional time will be required for instructional preparation, follow-up with i3 Scholars, and feedback from i3 Leadership. The summer institute schedule, a detailed curriculum outline, and teaching resources will be provided by i3. With assistance from i3 Faculty and Staff, Teaching Fellows will be responsible for developing and delivering syllabi, as well as the daily, in-class content of their respective modules.

PhD Teaching Fellows are required to live in housing provided by i3 as part of our in-residence, living-learning community model. Because i3 is an immersive, community-oriented program, we strongly encourage Fellows to engage in i3 activities, such as meals, evening activities, and weekend trips, and participate in both structured and unstructured interactions that develop naturally as part of living on-campus alongside Scholars and i3 Leadership. The most successful Teaching Fellows have been those who are present throughout the program outside of their regularly scheduled teaching time. Fellows also have the chance to foster meaningful connections with the i3 Core Team, visiting Research Advisors, i3 presenters, and faculty at one of the many academic institutions that call Austin home through optional scheduled meetings.


Module Descriptions

Research Design

Our Research Design Module introduces students to research design, including the different approaches and the types of knowledge that can be generated based on how research is designed and carried out. PhD students with expertise in qualitative, quantitative, or mixed methods approaches or those with a working knowledge of different research methodologies and their theoretical underpinnings are welcome to apply. As a PhD Teaching Fellow for this module, you will be tasked with:

  • Introducing students to the process of designing research studies
  • Demonstrating how each part of research design informs the next (from the research questions to the methods to dissemination)
  • Exposing students to an overview of different types of research methodologies, including the strengths, weaknesses, and ethical considerations of each
  • Developing hands-on activities to encourage students across disciplines to connect their  interests to the information sciences and explore the role research plays in understanding complex problems and informing solutions


Computational Thinking & Tools

Our Computational Thinking & Tools Module introduces students to tools and practices that they can use in the process of conducting research and succeeding in graduate school. PhD students from a variety of backgrounds should consider applying to teach this module, but students who have a wide exposure to a variety of tools (both computational and not) for data collection, analysis, and writing are encouraged to apply. As a PhD Teaching Fellow for this module, you will be tasked with:

  • Introducing students to computational thinking, particularly how to turn a complex problem into one that is understandable and can be worked through
  • Demonstrating how technology can be used to understand problems and help build solutions in a research context (project management, data collection / analysis, data visualization, dissemination)
  • Exposing students to tools to aid in these processes and providing hands-on practice applying and using these tools
    • Example tools include but are not limited to: 
      • Slack / Asana for Project Management
      • Python (Twitter scraping) / Tweepy / Qualtrics for Data Collection and Analysis
      • Tableau / R for Data Visualization
      • Twine / web design for Dissemination, etc.
  • Explaining which tools to use and when, their strengths, weaknesses, and limitations as well as ethical considerations of using these tools


Compensation and Benefits

Teaching Fellows will receive a $1,000 honorarium and up to $250 for course supplies and materials. Further, travel expenditures to/from Austin will be paid for by i3. Housing arrangements will be made in University of Texas at Austin campus housing and provided by i3 at no cost to Teaching Fellows.

Teaching Fellows will also be provided with work space, access to our labs, access to the University’s libraries, access to office supplies and equipment, and the support of our administrative staff.

i3 Teaching Fellows have the opportunity to leave with:

  • Teaching Experience. i3 Teaching Fellows will get hands-on experience teaching undergraduate students from diverse backgrounds, majors, and institutions, which will better prepare them for teaching-oriented careers.
  • Community. By living alongside i3 Scholars and Leadership, Teaching Fellows get the chance to form meaningful and lasting connections with the i3 community. Additionally, Fellows are introduced to a network of over 210 i3 Alums & ~150 i3 Leaders in Academia & Industry across the country.
  • Mentorship and Professional Development. i3 Teaching Fellows have the opportunity to build relationships with multiple mentors, including i3 Leadership and other faculty members. Fellows participate in professional development sessions and receive personalized, daily feedback.




  • Applicants must have completed one semester of coursework at the doctoral level
  • Applicants must be U.S. citizens, permanent residents, or DACA recipients


  • Applicants should have experience working with students from a wide variety of disciplinary backgrounds and documented experience working in a diverse, multicultural teaching and research environment
  • Applicants should ideally have the long-term goal of becoming a faculty member at an iSchool or similar institutional context
  • Doctoral students at iSchools will receive priority consideration
  • Applicants should be able to demonstrate a commitment to diversity and increasing opportunities for underrepresented populations


Application Materials

Application packages should include:

  • A cover letter: Applicants should indicate in their cover letters their preferred teaching module (i.e., Computational Thinking & Tools or Research Design) and describe their qualifications for teaching this module, ability to be part of an immersive community like i3, and willingness to contribute to diversity and inclusion.
  • CV
  • 2 academic references (names and contact information)
  • OPTIONAL: If applicable, applicants may submit course evaluations or a letter from a faculty member attesting to the applicant’s teaching excellence.

To apply, submit all materials via the Application page.


The University of Texas at Austin prohibits and will not engage in discrimination or harassment on the basis of race, color, religion, national origin, ancestry, sex, age, marital status, familial status, sexual orientation, gender identity and expression, genetic information, disability, or status as a veteran.