“If you are interested in the application of machine learning to image classification in gas emission detection, this is the right opportunity for you. Be a part of the team of research and machine learning scientists and get mentored by some of the best minds in AI.”
This is a paid residency that will be undertaken over a twelve-month period with the potential to be hired by our client, Kuva Canada, afterwards (note: at the discretion of the client). The resident will report to an Amii Scientist and regularly consult to and work with the Client team to share insights and engage in knowledge transfer activities.
Kuva is leading a revolution in the detection and measurement of methane emissions for the reduction of greenhouse gas emissions in the oil & gas industry. We are providing an end-to-end solution including a cloud based emissions monitoring platform with emissions alerting service as well as a low-cost, automated infrared camera for gas detection. Leveraging our proprietary platform technology, our solution enables our customers to receive emissions alerts, reports and analytics based on images of methane emissions at the best price-performance ratio in the industry. Kuva enables the oil and gas industry to dramatically reduce emissions and at the same time improve site operations.
Kuva Canada is based in Calgary, AB and is a subsidiary of Kuva Systems, headquartered in Cambridge, MA. Applicants located in (or willing to relocate to) Alberta will be given preference, but remote applicants within Canada will be considered.
The Kuva infrared imaging system automatically detects and measures emissions, delivering direct image-based alerts. Those images of emissions, annotated with quantified release metrics, are then transferred via the cloud to customers’ work order management and production operation systems. Armed with this actionable information, customers can implement mitigation plans without the need to conduct secondary manual inspections. An example image is shown below.
The focus of this project is to develop a machine learning solution that minimizes the occurrence of false positive detections and eliminates the need for human reviewers. Currently, relatively high false positive rates are mitigated by human reviewers that confirm the presence of gas using a diagnostic visualization of the image data. Machine learning may be able to operate on the same features used for the diagnostic image to automate much of this screening process. Kuva has a large data set of labeled data that will form the basis of algorithm development.
Are you passionate about building great solutions? Do you want to drive a high impact business? You’ll be presented with opportunities to both personally and professionally develop as you build your career. We’re looking for a talented and enthusiastic individual with a solid background in machine learning, specifically computer vision.
Besides gaining industry experience, additional perks include:
If this sounds like the opportunity you've been waiting for, please apply by July 15! Please include your cover letter and resume with the application.
Amii is proud to be an equal opportunity employer. We are committed to creating a diverse, inclusive and excellent workforce.
Nov 22nd 2023
On October 17, Dr. Deepa Krishnaswamy, from Boston's Brigham and Women's Hospital, presented “AI-derived annotations for lung cancer collections using NCI Imaging Data Commons" at the AI Seminar.
Nov 16th 2023
Thinking of pursuing a PhD? Amii researcher Alona Fyshe explores how undertaking a PhD is like training for the Olympics, and how you can develop an Olympian state of mind.
Nov 16th 2023
Read our November monthly update on Alberta’s AI ecosystem. Featured this month: Impact Report & New U of A Faculty Positions.
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