URSSI Welcomes Second Cohort of Early-Career Fellows
Nic Weber and Kyle Niemeyer • September 23, 2025
We are happy to announce a second cohort of the US Research Software Sustainability Institute (URSSI) Early-Career Fellowship. This cohort includes three projects and five fellows working on the follwoing:
Characterizing LLM-Generated Code in Scientific Software - Shahan Ali Memon, David Farr, and Eva Maxfield Brown will investigate the detection of AI assisted development in code repositories that are linked to scientific articles. Their project will evaluate existing methods used for detection (e.g. code stylometry), create a dataset of verified AI/non-AI assisted code, and assess how adoption changes code quality, documentation practices, and reproducibility.
Call for Proposals: URSSI Early-Career Fellows (Round 2)
Kyle Niemeyer and Nic Weber • July 2, 2025
The US Research Software Sustainability Institute (URSSI) invites new applications for an Early-Career Fellowship program.
This fellowship offers funding support between $10,000 and $25,000 for research in one of the following areas: AI/ML Integration in Scientific Software Development, Scientific Software Sustainability, or Software Education Research.
The fellowship is open to PhD students, postdoctoral researchers, research software engineers, and research scientists who are less than three years removed from their final degree or appointment.
Applications open for 2025 Reproducible Machine Learning Workflows for Scientists Workshop
Matthew Feickert • June 27, 2025
Doing interesting research can be hard, and having to carefully curate a complex software stack of tools by hand or debug why your software environment broke when it worked two days ago can make it even harder. Luckily, we don’t have to make research harder than it needs to be!
Scientific researchers need reproducible software environments for complex applications that can run across heterogeneous computing platforms. We now have modern tools for creating fully reproducible hardware accelerated software environments for machine learning workflows (and other scientific applications that use CUDA) that use high level semantics aimed at researchers!
Applications open for 2025 Summer School in Open Science + Research Software Engineering
Madicken Munk, Joseph H. Kennedy • June 3, 2025
Do you want your science, research, and software to be open and accessible? Do you use or develop software in your research? Do you have some foundational skills and would like to build on and expand them?
If this sounds like you, then you might be interested in the upcoming Summer School in Open Science and Research Software Engineering. In August 2025 we will be hosting a five-day workshop on open science and research software engineering at the University of Alaska Fairbanks and organized in collaboration with the Alaska Satellite Facility and the Geophysical Institute.
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