DH & RSE Summer School 2026

DISKAH will introduce its Fellows to a week-long training programme during the DH & RSE Summer School 2026 exploring the intersection of digital humanities and research software engineering. Participants will gain an invaluable insight into the roles and practices of Research Software Engineering in Digital Humanities research.

The Summer School is co-organised by the Software Sustainability Institute, King’s College London, University of Cambridge and University of Edinburgh, in collaboration with the Digital Skills in Arts and Humanities (DISKAH) project.

For any questions about the summer school, please get in touch with DH-RSE@manchester.ac.uk

Programme

The full programme of the summer school can be found here. On Friday 3 July 2026, we have scheduled an additional DISKAH day for our fellows. The programme for this additional day can be found below:

Friday 3 July 2026

Time Session

9:00 - 9:30 Coffee/tea 

9:30 - 9:45 Welcome – Introduction to the day

9:45 - 11:00 Mapping your research workflows (data, tools, code, pipeline) 

DISKAH Team

11:00 - 11:15 Morning break 

11:15 - 12:15 Onboarding to HPC 

DISKAH Team

12:15 – 13:15 Lunch break

13:15-14:15  Using HPC more efficiently 

DISKAH Team

14:15-14:30  Afternoon break 

14:30-15:30  Using HPC more efficiently 

DISKAH Team

15:30-16:00  Wrap up and end of day 

Venue

The summer school will take place at Booth Street East, University of Manchester. Booth Street East is just off Oxford Road, with excellent public transport links and a wide range of food, drink and accommodation options around. More information can be found here.

Travel and accommodation

Travel and accommodation for the Fellows is arranged by the DISKAH administrator. Please contact L.Johncox@brighton.ac.uk and J.Gandey2@brighton.ac.uk if you have any questions.

Meals

Catering will be provided throughout the summer school.

Software, Hardware and Data

All Fellows will need to bring their own laptops to the training. You should have user rights to install software on the laptop. It will also be good to bring a sample of your dataset to have available during the training.