We are looking applications for a fully funded PhD student, to work at the intersection of disease ecology and artificial intelligence.

All of these positions are part of a seven years program on using modern artificial intelligence techniques to develop a unified knowledge base for ecology and evolution; this build on previous research on AI for automated ecological synthesis (read it before applying). In addition, please read the lab’s values and philosophy before applying.

The project in a nutshell: with recent advances in artificial intelligence, bridging probability theory and logic theory, we have a chance to (i) formalize our knowledge about ecological systems in quantified statements, (ii) embed these statements in a densely connected knowledge graph that will draw links between distant sub-fields, and (iii) use existing open data to validate and weigh the veracity of these statements. If successful, this will lead to a rich knowledge representation that might reveal there are, after all, general laws in ecology. The research axes identified for this effort will focus on (i) public health concerns related to disease emergence and re-emergence, and (ii) changes in species distributions under climate change and the subsequent re-wiring of species interaction networks.

All positions are fully funded, and come with yearly support for travel, open access publication, and computer equipment. All positions also come with free access to Compute Canada infrastructure, including a GPU cluster, and training sessions on advanced research computing.

Fellows selected as part of this project will also be involved in organizing and TA-ing two intensive classes on artificial intelligence for biodiversity science, and one symposium on the same topic followed by a two-days writing retreat (all activities are fully funded). All applicants will get the opportunity to mentor undergraduate research assistants as well as graduate students from our MSc in Quantitative and Computational Biology.

This research program is by nature pluri-disciplinary. Candidates with only a subset of the preferred qualifications are encouraged to apply. All applicants are expected to have a robust foundation in either applied mathematics or scientific programming, and an interest for biodiversity, or a robust foundation in biodiversity and an interest for mathematics and programming. At no points will grades or journal impact factors be considered as a measure of the quality of an applicant.

Please email the application materials in a single PDF file (named lastname.pdf) to timothee.poisot@umontreal.ca, with the subject “General laws: name of the position”. Review of applications will start immediately, and applicants will be interviewed on a rolling basis unless the positions are filled. Applicants, especially for the PhD fellowships, who do not have published articles, can instead write a short summary of the most exciting research project.

Type
PhD position
Institution
Université de Montréal
City
Montréal
Country
Canada
Closing date
October 1st, 2019
Posted on
August 30th, 2019 14:33
Last updated
August 30th, 2019 14:33
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