Summer 2026 Teaching Fellow – RISE Data Science
Boston University Summer Term seeks Teaching Fellows to work 7 weeks for the Practicum track of the precollege Research in Science & Engineering (RISE) program in summer 2026. The focus of the RISE: Practicum 2 course is Data Science.
The RISE Practicum is a six-week, non-credit program for exceptionally talented rising high school seniors. Students are introduced to undergraduate-level research projects while previewing college life. The program combines instructor-led lectures and afternoon labs with the opportunity to conduct one of several styles of computational research: time series analyses (e.g., forecasting), statistical method benchmarking, or scientific software development. Making use of data from the neurosciences, environmental science, physics, economics, and urban planning, students will learn essential statistical and coding skills. This includes a wide set of computational modeling approaches, uncertainty quantification skills, and frameworks for reproducible scientific computing. The program concludes with student group presentations on the outcomes of their research projects at a Poster Symposium.
Below are the weekly schedule and compensation for the position:
- May 20: 2 hours of instructional training
- Week 1 (June 23-26): 2 hours of course prep
- Weeks 2-7 (June 30 – August 7, Tuesdays-Fridays): 20 hours worked per week (4 days/week; 5 hours/day; 6 weeks)
- Total compensation: $5,526.68
- Calculated by the hourly rate established in the BUGWU contract for summer 2026, which is to $44.57 per hour.
- Summer Term Pre-College Programs will serve as a funding source during weeks 1-7 of the position. The total pay will be divided equally over weeks 1-7.
Additional skills:
- Proficient in at least one scientific programming language, such as Python, Matlab, or R.
- Familiarity with version control (GitHub) and unit testing in language of choice.
- Willing to learn a baseline level of Python within a short time frame, if not already comfortable.
- Familiar with mathematical probability and statistics (equivalent to BU’s CAS MA 581, CAS MA 582 or CAS MA 681).
- Experience with time series data analysis or simulation in one of the following fields: environmental science, population ecology, psychology/neuroscience (e.g.,
calcium imaging, fMRI, LFP/ECoG/MEG/EEG), economics, survival analysis (e.g., insurance, health care), queuing theory, digital text analysis (e.g., rolling topic
modeling). Other fields that provide exposure to standard time series models from any field are acceptable and should be indicated in the provided application. - Be able to regularly facilitate discussions and answer basic Python questions from high school students based on the assigned reading and lectures about statistics and probability.
- Work with other teaching fellows and instructors to manage student learning and research projects, being the primary supervisor of 1-2 small groups.
- Experience with formal training in one of the following is a plus: principles in classical machine learning (e.g., dimensionality reduction, gradient descent) and
non-parametric analyses (e.g., bootstrapping) are a plus.
Those interested in the position should send an email to Amanda Wein (kautzman@bu.edu) and Ursula Imbernon (uimberno@bu.edu) directly. In the email, please describe your teaching experience and include your CV as an attachment. Thank you!