- Programming: R, RShiny, basic Python
- Statistical Methods: Spatio-temporal modelling, Bayesian inference, Hidden Markov models, non-linear modelling, hierarchical modelling, simulation-based inference
- Data Visualisation: ggplot2, gganimate, plotly, leaflet
- Data Wrangling: comfortable with tidyverse and base R approaches; experience using SQL (SQLite via R)
- Teaching & Communication: In-person and online delivery, course coordination (ca. 150 students), course administration, interactive and accessible teaching of complex methods, supervision of postgraduate and PhD students
- Reproducible Research: RMarkdown, Quarto, version control (Git), simulation workflows, reproducible project structure
- Version Control: Git (via GitHub and GitHub Pages)
- Markup & Documentation: RMarkdown, LaTeX, Quarto
- APIs & Data Integration: Working with RESTful APIs, JSON parsing, ORCID integration
- Languages: English (Fluent), Afrikaans (Fluent), Spanish (Basic)
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