Postdoctoral Fellowship Position in Assessment of Wildfire-related Risks and Hazards Using Computer Vision
ENG Civil Engineering
Competition No. – A104147265D1
Closing Date – March 31, 2022
This position has an end date of one year from the date of hire, with the possibility of extension, and offers a comprehensive benefits package which can be viewed at: Postdoctoral Fellows Benefits Overview
One postdoctoral position is available immediately to support the research conducted by Dr. Mustafa Gül and his team on sustainable and smart cities and communities focusing on wildfire-risk assessment using computer vision. The candidate will work on assessment of wildfire-related risks and hazards to critical infrastructure systems using image/video processing, Artificial Intelligence (AI), and deep learning, and must demonstrate their ability to integrate these skills. The position is available for one year with possibility for renewal.
The candidate should possess:
Ph.D. degree in Computer Science/Computer Engineering/Electrical Engineering or related fields.
Experience with assessment of wildfire-related risks and hazards
Experience in AI/deep learning, image/video processing, data analytics, signal processing
Strong programming skills and familiarity with related software and programming languages
Strong data analytics and management skills and ability to develop databases
Experience with GIS
Strong publication and presentation track record in related fields
Experience and interest in mentoring and training students as part of a research team
Ability to work independently and within a team, including demonstrated leadership qualities and interaction with collaborators
Excellent verbal and written communication skills, with ability to present to a wide range of audiences
Application Instructions:
Please apply with a cover letter, CV, research statement, and contact information for three references.
To assist the University in complying with mandatory reporting requirements of the Immigration and Refugee Protection Act (R203 (e)), please include the first digit of your Canadian Social Insurance Number in your application. If you do not have a Canadian Social Insurance Number, please indicate this in your application.
Applications will be considered immediately until the position is filled.
How to Apply
Please apply using the University of Alberta careers page at: https://www.careers.ualberta.ca/Competition/A104147265D1/
Note: Online applications are accepted until midnight Mountain Standard Time of the closing date.
OVID-19 Vaccination: Proof of full vaccination against COVID-19 in compliance with the University’s COVID-19 Vaccination Directive. Fully Vaccinated means a status an individual achieves 14 days after having received the recommended number of doses of a COVID-19 vaccine approved by Health Canada or the World Health Organization, and requires the individual to maintain the recommended number and type of vaccine doses as updated and required by Health Canada thereafter.
