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SnB 2025 Shortcourse Slides: Good Software Engineering Practice for R Packages

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Short course: Good Software Engineering Practice for R Packages

SnB 2025, Paris, France

Friday 10 October, 2025 14:00 - 17:00 CEST

Join us for an engaging half-day face-to-face short-course designed to enhance your R programming skills with a focus on developing reliable R packages used in statistics or data science. This course is a blend of informative presentations and hands-on coding parts, aimed at equipping participants with practical tools and techniques for engineering high-quality R packages. This course is tailored for individuals who are already comfortable with writing functions in R and are looking to elevate their package development skills. Bring your laptop and be prepared to transform your approach to R package development through hands-on learning and collaboration. Whether you're looking to improve your workflow, meet regulatory standards, or simply enhance the quality of your statistical tools, this course offers valuable insights and skills to achieve your goals.

Speakers

Daniel Sabanés Bové

Daniel Sabanés Bové studied statistics at LMU Munich, Germany and obtained his PhD at the University of Zurich, Switzerland in 2013 for his research work on Bayesian model selection. He started his career in Roche as a biostatistician for 5 years, then continued at Google as a data scientist for 2 years, before rejoining Roche as a statistical software engineering lead for 4 years. In 2024, Daniel co-founded RCONIS (Research Consulting and Innovative Solutions). He is (co-)author of multiple R packages published on CRAN and Bioconductor, as well as the book “Likelihood and Bayesian Inference: With Applications in Biology and Medicine”. He is currently a co-chair of the openstatsware working group on Software Engineering in Biostatistics.

Jack Talboys

Jack Talboys is a software developer at Novartis. He graduated from the University of Bath with a BSc in Statistics in 2020. Since then, he spent 4 years working as a Data Scientist for a data consultancy, building R and python-based tools to help companies in a wide range of industries. In April of 2024 he joined the Open-source enablement team within Novartis as a Software Developer. In this role he has worked closely with study teams to help implement improved coding practices, as well as producing R packages and shiny applications to help study teams do their best work as efficiently as possible. He is interested in helping study teams utilise Open-source and contributing back to Open-source himself.

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