“We are a growing company looking for talented, dedicated people interested in solving challenging problems for our clients.”
Assist in the implementation of geospatial ecological simulation models, managing code used across multiple projects. Contribute to current R package development, project workflows, and the development of standardized analyses of geospatial data and model outputs.
This is a full-time position for 12 months with possibility of extension.
1. Implementation of dynamic landscape simulation models and analyses in R;
2. Enhancement, testing, optimization, and documentation of model code across multiple projects;
3. Synthesize and visualize model outputs, generate maps and figures for summary reports.
Required skills and qualifications
Relevant Bachelor’s degree (e.g., computer science, geography), or equivalent combination of education and experience (e.g., BSc in Biology/Ecology and MSc with focus on ecological modelling);
Demonstrated expertise in geospatial analysis in R ;
Experience with reproducible workflows, version control and management (git, GitHub);
Excellent communication and analytical skills;
Strong attention to details and excellent organizational skills;
Able to work under pressure and meet deadlines;
Ability to adapt to a changing environment and handle multiple priorities.
Experience with other programming languages (especially C++, python);
Experience with Ubuntu Linux and comfortable working from commandline;
Experience with R package development;
Experience building interactive web-based applications and visualizations with R shiny, especially for geospatial applications;
Experience with geospatial databases (e.g., PostGIS).
Proof of full vaccination against COVID-19.
About FOR-CAST Research & Analytics:
FOR-CAST Research & Analytics develops ecological simulation software and forecast models for government and industry to inform decisions related to land management and species at risk. Our team is experienced working with large scale spatial and ecological data, developing statistical and process-based simulation models, and are passionate about delivering reuseable data-oriented workflows. We coordinate with reseachers from various ecological disciplines to support ecological modelling and forecasts. We strive to support our clients in academia, government, and natural resource management make vital management decisions using the best available scientific data and models.