Research Fellow – Mathematical & Computational Ecology
Core
Design and develop computational and statistical tools to forecast the stability of ecological communities under environmental change.
Role type
Research Fellow (Mathematical & Computational Ecology)
Builds
Novel computational frameworks for forecasting forest ecosystem responses to disturbance.
Domain
Ecology, Statistics, Machine Learning
Deliverable
production ML models
Required skills
Bayesian hierarchical modelling, parametric statistics, machine learning, dynamical systems, deep learning, scientific computing, advanced programming, large-scale dataset analysis
Preferred skills
biological or environmental data experience, community ecology, forest ecology, theoretical ecology
Technologies
Bayesian hierarchical modelling frameworks, machine learning libraries, dynamical systems solvers
Responsibilities
Design and develop new statistical approaches for forecasting ecosystem stability, combine tools from parametric statistics and deep learning, benchmark novel approaches against real-world datasets, move fluidly between methodological frameworks
Seniority
Research Fellow (PhD required)
