Skip Navigation

Working at MIT offers opportunities that just aren’t found anywhere else, including generous and unique benefits that help to ensure that MIT employees are healthy, supported, and enjoy a fulfilling work/life balance. Discover more about what it's like to work at MIT.

We welcome people from all walks of life to bring their talent, ideas, and experience to our community. We value diversity and strongly encourage applications from individuals from all identities and backgrounds – like yours. If you want to be part of our exceptional, multicultural, collaborative, and inclusive community, then take a look at this opportunity.

Research Scientist 1
  • Job Number: 24927
  • Functional Area: Research - Other
  • Department: Comparative Media Studies/Writing
  • School Area: Humanities, Arts, & Social Sciences
  • Employment Type: Part-time Temporary (Remote Only)
  • Employment Category: Exempt
  • Visa Sponsorship Available: No
  • Schedule:


Posting Description

RESEARCH SCIENTIST 1, Comparative Media Studies/Writing, to work closely with DC public schools as part of an NSF DRK-12 Research-Practice Partnership (RPP) titled: Designing Computational Modeling Curricula across Science Subjects to Study how Repeated Engagement Impacts Student Learning throughout High School (DC-Models). Will collaborate with a larger team to organize and conduct mixed methods research with a large urban district including district-level leaders and teachers to explore integration of computational thinking in science classes; and build and maintain relationships with district leaders and teachers through regular communication (e.g., site visits & email) and provide dignity-affirming care (~1 hour/week).

Job Requirements

REQUIRED: Ph.D. in Learning Sciences, Science or STEM Education, or related fields; robust organizational skills and time management skills; experience with design-based research including the design of learning environments (e.g., STEM curriculum, software) to develop theories about learning in the authentic learning contexts; robust background in qualitative analysis, including analysis of video data, interviews, and artifacts to build evidence-based claims for learning; deals with confidential information and/or issues using discretion. PREFERRED: Robust background in science education and Learning Sciences research with understanding of computation and modeling in science learning; subject area expertise in Math, Science and/or agent-based modeling; knowledge of current research in modeling (including computational modeling), and inquiry-based science education; experience with classroom teaching; experience working on a Research Practice Partnership (RPP); experience designing or facilitating professional development for K-12 STEM teachers; familiarity with NGSS and aligned curricula; basic experience with Learning Analytics; and robust writing skills. Job #24927

This is a temporary, one-year 50% FTE position. The position may be extended for an additional year based on mutual interests and needs. Early career applicants are encouraged to apply.

The position is based in the Washington, D.C. area and entails frequent site visits to DC public schools. A candidate should be able to arrange their own transportation to the schools.

4/25/2025