Job Description

Opportunity Brief Description:

The Al Machine Learning Research Internship application is now open, Borealis AI, a research institute dedicated to AI and machine learning, has received support from the Royal Bank of Canada. The institute is staffed by exceptional AI researchers and engineers who are passionate about solving intelligence problems. Borealis AI is at the forefront of advancing machine learning science and developing innovative financial services products. Their research has been published in over 40 prestigious academic venues, covering topics such as deep learning, reinforcement learning, language processing, and AI safety. Established in 2016, Borealis AI has four labs in Canada and boasts a team of over 100 experts.

Borealis AI is planning for a hybrid work environment for its internship programs during the Winter 2024 term. Interns will be involved in supporting research on diverse theoretical and applied machine learning projects. Joining Borealis AI will provide interns with exclusive access to extensive structured and unstructured datasets, along with the essential tools and resources required to create revolutionary statistical models. Being a part of the team means interns will get the chance to publish original research in peer-reviewed academic conferences, including NeurIPS, ICLR, ICML, CVPR, and collaborate with some of the most brilliant minds in AI.

 Details:

Organized by: Borealis AI

Eligible Nations: International

Format: Hybrid (Online, Offline)

Deadline: September 4, 2023

Gender: Male and Female

Internship Duration: 4 months (January – April 2024)

Locations: Canada (Montreal, Toronto, Vancouver, Waterloo)

Eligibility Criteria:

The Winter 2024 term internship program at Borealis AI seeks candidates who possess the following qualifications:

• Proficiency in implementing cutting-edge machine learning techniques.
•  Strong motivation to tackle complex research problems.
• Passion for working with data, algorithms, and statistics.
• Enrollment in a graduate program in Computer Science, Engineering, or a related mathematical field (e.g. Physics, Math, Statistics, etc.).
• Previous experience publishing at top-tier AI conferences.
• Experience writing modular, scalable software in Python.
• Familiarity with Unix command line and bash scripting.
• Proficiency in deep learning packages such as Tensorflow, Keras, and PyTorch.
• A thorough understanding of machine learning algorithms and/or statistical modeling.

Internship opportunities areas:

• Privacy and Fairness;
• Unsupervised and Semi-supervised Learning;
• Bayesian Optimization;
• Deep Learning;
• Reinforcement Learning;
• Graphs and Optimization;
• Time Series Forecasting;
• Computer Vision
• Natural Language Processing;
• Interpretability and Explainability;
• AutoML;

How to Apply 

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