Public page for the WEHI Research Computing Platform (RCP)
The WEHI Research Computing Platform regularly provides unpaid internship opportunities via the Discovery Internship Program. Interns can get course credit through the University of Melbourne Data Science and Software Engineering programs, as well as Open Source Contributors from around the world. These internships are 100% remote.
We have won a WEHI award - the Kellaway Excellence Education Award in 2024 - for being innovative and putting interns first. This is why we have:
We have three intakes per year - Semester 1 (March to May), Semester 2 (August to October), and Summer (November to February the next year). The intake dates currently available and hours per week are here. We have anywhere between 20 and 45 interns in an intake.
Please note that applications for the Summer 2025 / 2026 intake have now closed.
Here are some of the recurring student intern projects and new projects we are working on.
Sign up for Semester 1 2026 updates
We have had 251 interns through the program since Semester 2, 2021 who have provided over 24 person years of effort to help us uncover and document complexity early in over 80 intern projects.
Out of the 16 anonymous reviews that have been given by students as at 4th of June 2025, our internships have been rated a 4.6 out of 5.
Before you apply - please ensure you can take the time to spend doing at least 6 to 8 hours per week on these internships:
Also please ensure you:
We prepare students for the real-world by teaching them:
We even tell students how to try to avoid the top 5 mistakes that students make.
In our Welcome Session, we talk about ways you can better learn real world skills.
Many of the projects work in the Data Analysis and Research Software Engineering space using High Performance Compute (HPC). We work across diverse projects such as imaging, cryo-EM, genomics, transcriptomics, clinical informatics, and capacity planning.
We mainly work with projects that use R and Shiny, Python, Julia, bash, while also making the most out of other technologies such as RStudio, Jupyter notebooks, PowerBI and other applications within the data analytics space.
Here are some of the previous student intern reports.
Sometimes, we are in contact with students who cannot get course credit and are extremely keen to volunteer as an open source software contributor. In these situations, we have to be careful we do not act in an exploitative way. This is why we have written our expectations of potential open source contributors to make the expectations more transparent.
You can listen to two students talk about their projects (click image below).
Here is more information about the internship program: