Mechanistic Modeling

Model philosophy: Model design, model implementation, analytical solution of models, model simulation, model-data integration, model testing and evaluation

Model types: differential equations, dynamical systems, game theoretic models, partial differential equations, integrodifference equations, deterministic and stochastic models, spatial models, simulation models including agent-based models, and more.

Statistical Modeling

Frequentist methods: linear mixed models, generalized linear mixed models, logistic regression, principal components analysis, parametric and non-parametric techniques, analysis of covariance, blocking, nested analysis of variance and more.

Bayesian inference methods: multivariate models, interaction terms, Markov chain Monte Carlo methods, model comparison techniques including AIC and BIC.

Complex Dataset Analysis

Including analysis of data with large numbers of plots, species, and individual observations, dozens of variables, variable interactions, time-series, zero-inflated data, and more.

Programming

Languages include R, C++, Python, Mathematica, MATLAB, and Stan

High Performance Computing

Server management, parallel computing, version control, job scheduling systems, Unix

Experimental Design

Scientific method, controlled experimental design, hypothesis testing, field ecology