Currently no more positions are available.

New PhD positions on AI and theoretical ecology are open.

The students will be involved in the EcoSim project. We have conceived EcoSim, a versatile simulation platform that has been designed to investigate several broad ecological questions, as well as long-term evolutionary patterns and processes such as speciation and macroevolution. This tool generates a huge amount of data representing all the events, the mental states and actions of every agent saved for every time step of every run. This thorough tracking system allows for a deep statistical analysis of the whole system using several dedicated tools that we have conceived to extract, to measure and to correlate parameters that could be useful to understand the underlying and emerging properties of such a complex system. This level of detail is the highest advantage of this approach compared to real data gathering which is highly limited by the large spatial and temporal scale involved in ecological questions. All the results we have already obtained demonstrate high potential for our approach to handle complex ecological questions, showing evolutionary and ecological phenomena and patterns conform to real observations and giving the possibility to investigate many hypothesis in a reasonable amount of time.  This simulation is now the framework for the study of numerous specific ecological questions in collaboration with biologists. For example, this approach will be used to study complex ecological and evolutionary processes such as the species abundance distribution, patterns and rates of speciation, the evolution of sexual and asexual populations, the interaction and diffusion of an invasive species into an existing ecosystem, etc.

Due to the highly interdisciplinary framework of the project we need to find very motivated students prepared to learn numerous concepts coming from AI, biology and philosophy. However, the environment for this project will be very supportive has our team is already composed of computer scientists and biologists. We also work in close collaboration with biologists from the University of Windsor and the Great Lakes Institute for Environmental Research. Having knowledge in machine learning or in evolutionary ecology would be advantageous. Having a strong experience in C++ programming is highly recommended.

Contact information:
Dr. Robin GRAS
Associate Professor, Canada Research Chair
School of Computer Science
Cross-appointed by the Biological Department