Project Canary is a Colorado-based B-Corporation that provides real-time emissions monitoring to energy and landfill companies in order to reduce greenhouse gasemissions. We’re looking for an applied mathematician or atmospheric scientist who can apply their scientific and/or mathematical expertise to the following problems to help us on our mission to reduce emissions (via an NSF-funded grant):
1) Signal processing for spectroscopy
2) Atmospheric or computational fluid mechanics and chemical transportsimulation
3) Data analytics of field data from atmospheric and chemical sensors
Having an understanding of (or a willingness to brush up on) inverse methods, Bayesian inference, and/or signal processing would be helpful. Additionally, having coding or data processing experience and being comfortable in a Unix or other cloud-based HPC environment is desirable.
Project Canary (http://projectcanary.com/) is a mission-driven B-Corp that independently assesses the carbon and environmental footprints of carbon-intensive industries like oil and gas. Project Canary achieves this by ingesting data from a wide variety of sources, including its own environmental sensors, to calculate carbon emissions from different facilities in real-time. Currently, large swaths of the chain have no direct measurements. With hundreds of environmental and air quality sensors currently deployed around the country, Project Canary can definitively claim that not all facilities are created equally.
For additional information, please see the attached flyer.