Mathematical and statistical

• Regression techniques including robust regression, nonlinear regression, generalised linear models, generalised additive models, mixed effects models and support vector regression
• Bayesian inference using integrated nested Laplace approximation
• Machine learning including decision trees, random forests, neural networks and deep learning
• Simulation modelling of complex systems
• Image processing, remote sensing and GIS
• Time series analysis and forecasting

Programming

• R statistical programming and package development
• Programming languages include C, C++, Python, Java, Javascript, Typescript and SQL
• Document formatting languages include LaTeX, HTML and CSS
• Cross compilation and linking of different languages and software to balance efficiency and accuracy
• New languages and software learnt quickly and easily as required

Research and innovation

• Problem scoping and agile development
• Design, development and adaptation of experimental methods to produce new techniques and enhanced results

Communication

• Communication of complex concepts clearly through discussion, demonstration and, when required, by developing specific visualisations and computer apps.
• Clear, concise, and accurate writing for academic, business and general audiences.