Now Hiring: Machine Learning Intern - Canada Wildfire

“If you are interested in the application of machine learning to predict extreme fire weather, 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.”

-- Jubair Sheikh, Machine Learning Scientist and Mara Cairo, Product Owner, Advanced Technology


About the Role

This is a paid internship that will be undertaken over a six-month period with the potential to be hired by our client afterwards (note: at the discretion of the client). The intern will be reporting to an Amii Scientist and regularly consult with the Client team to share insights and engage in knowledge transfer activities. At the end of the engagement, it is expected that the work will be publishable to a respected conference or journal.

About our Client

The Canadian Partnership for Wildland Fire Science (Canada Wildfire) was initiated in June 2009, through a Memorandum of Understanding signed by three founding partners: Alberta Agriculture and Forestry (AAF), University of Alberta School of Forest Science and Management (UofA), and the Canadian Forest Service (CFS) Northern Forestry Centre (NoFC). Originally known as the Western Partnership for Wildland Fire Science, it was formed to address priority research needs by creating a fire science hub that linked AAF and NoFC with researchers at the UofA and other Canadian and international research institutions.

About the Project

In Canada, wildfires burn on average 2.5 million hectares annually. Three percent of these fires - that typically burn under extreme weather conditions - are responsible for 97 percent of the total area burned. Developing predictive tools for forecasting extreme fire weather is essential to manage fire and protect communities and other values on the landscape.

Canada Wildfire seeks a scientist to develop machine learning approaches to wildfire prediction with a specific focus on developing an early warning system based on forecasting extreme fire weather. This work could provide critical information in addition to the existing decision support tools used by fire managers to help better anticipate fire risk and allocate resources accordingly.

Required Skills / Expertise

We’re looking for a talented and enthusiastic individual with solid knowledge of machine learning and experience working with spatio-temporal datasets.

Key Responsibilities:

  • Clean and curate historical datasets
  • Perform exploratory data analysis
  • Build, train, and evaluate ML models
  • Develop Data and ML workflows
  • Undertake applied research on ML techniques to address the limitations in existing models
  • Collaborate with project team and stakeholders to develop MVP
  • Participate in regular meetings with the client, preparing presentations and reports

Required Qualifications:

  • Completion of a Computing Science or ML graduate program, MSc. or PhD
  • Research or project experience with computer vision and time-series methods
  • Solid understanding and experience in applications of deep learning techniques such as Convolutional neural networks, sequence models (RNN, Transformers, etc.) or multi task learning
  • Proficient in Python programming language and related ML frameworks, libraries and toolkits (e.g. Scikit learn, Keras, Tensorflow, PyTorch, Pandas, Jupyter notebooks)
  • A positive attitude towards learning and understanding a new applied domain
  • Must be legally eligible to work in Canada

Preferred Qualifications:

  • Previous experience applying machine learning to historical data
  • Familiarity with the atmospheric sciences domain
  • Publication record in peer-reviewed academic conferences or relevant journals in machine learning
  • Familiarity with time series anomaly detection methods like Autoencoders

Non-Technical Requirements:

  • Desire to take ownership of a problem and demonstrated leadership skills
  • Interdisciplinary team player enthusiastic about working together to achieve excellence
  • Capable of critical and independent thought
  • Able to communicate technical concepts clearly and advise on the application of machine intelligence
  • Intellectual curiosity and the desire to learn new things, techniques, and technologies

About Amii

One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

Why You Should Apply

Besides gaining industry experience, additional perks include:

  • Work under the mentorship of an Amii Scientist for the duration of the project
  • Participate in professional development activities
  • Gain access to the Amii community and events
  • Build your professional network
  • The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion)

How to Apply

If this sounds like the opportunity you've been waiting for, don’t wait for the closing date to apply!

Send your resume and cover letter indicating why you think you'd be a fit for Amii by June 3 through the Indeed listing.

Amii is proud to be an equal opportunity employer. We are committed to creating a diverse, inclusive and excellent workforce.

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