Speakers
Description
Developing software for astronomical data analysis is fundamental for both observers and theorists. As big data and large collaborations become the norm, astronomers must prioritise statistically rigorous, reliable, and maintainable software. High-impact research increasingly relies on open, reusable code, with 36% of recent Physics and Astronomy papers referencing software. Journals are also encouraging the publication of underlying code to enhance transparency and reproducibility.
Existing UK training initiatives in this field primarily target first-year PhD students, leaving a gap for later-stage researchers seeking advanced skills. ASTRODAT: AstroStatistics and Research-Oriented Data Analysis is a new week-long workshop, running from 8–12 September 2025, designed to bridge this gap. Aimed at early-career researchers, it will provide expert-led seminars and hands-on sessions on coding maintainable Python packages and applying advanced astrostatistics techniques. ASTRODAT will equip participants with the skills to develop robust, reusable software, fostering best practices in research-driven coding.
This poster will outline the workshop structure, curriculum, and logistics, as well as available funding opportunities.