Research Software Engineering

We want to help all researchers and students at UiT to develop and improve their research software. This can span from simple R or Python scripts to complex GPU enabled software packages.

Save time on your project by getting quick and comprehensive help by experts.

"I highly recommend this service to any researcher looking for reliable and efficient computational resources."

"Great support. Saved me weeks and weeks of time. Super helpful and friendly."

"RSE helped me adapt my analysis to run on the HPC computing cluster at UiT. This cut the time to run my analysis from many days down to hours."

(more testimonials)

Come to the weekly RSE HELP DESK

Get research data management and coding support from the University Library, the Research Software Engineering Group

UB is joing the RSE and HPC groups Wednesdays from 14:00–16:00 @UB244 for open help desk, where we aim to provide support for all UiT researchers and students to make their research more organized, reproducible and reusable.

The RSE group provides support for all code-related and high-performance computing topics, while Team Data from the Library will be there to answer all research data management related questions.

More details are available on the Tavla event page.

What we offer

Help with improving your scripts/code
- Code review: we look together at your code/script and give constructive feedback and advice
- Making code more reproducible and reusable
- Advice and help how to best document code
- Advice about whether to use YAML or CSV or JSON or TOML or something else
- Consulting and help with web development (static websites, JavaScript, HTML, CSS frameworks)
Help with organising your code
- Help with modularizing your code
- Help with moving your work/project/code/data to Git
- Help with Git, GitHub, and GitLab
- Help with organization of reusable and reproducible Jupyter notebooks and Binder

Help with sharing your code
- Help publishing your code
- Help with software licenses and open sourcing
- Packaging and sharing software
- Containerization (Singularity, Docker)
- Help with pip, PyPI, and Conda
Help with running your code faster
- Improving scaling, CPU, and memory footprint of research codes
- Porting to GPU
- Moving from local computer to cloud or high-performance computing (using e.g. NRIS resources)

If you have questions about code you wrote or want to write, please contact us or come and talk to us.