Video presentation

Target group

The IVADO “Scientist in Action” program aims at startups interested in hosting a master’s-level intern to advance an innovation project in artificial intelligence.

The master’s student participating in the program will complete a credited internship in addition to gaining entrepreneurial experience and exploring new career opportunities.


The program objective is to match talents to the entrepreneurial ecosystem. This is achieved by means of a credited applied research internship at a startup company.

The candidate acquires experience in the entrepreneurial environment and is in a better position to make career choices.

For the startup, the program offers a unique opportunity to access sought-after expertise at an affordable cost, while promoting its organizational culture and potentially recruiting a new team member.

Supported fields and examples of mandates

Any project involving artificial intelligence and its applications, for example:

  • Business intelligence
  • Operations research
  • Data science
  • Data visualization
  • NLP
  • Machine learning

For examples of mandates, here is a summary of some internship offers from previous editions.


Lerna AI

Federated Learning on Sensitive Mobile Data (Python/Java)

At Lerna AI we are building a federated machine learning platform for mobile applications. Our technology enables mobile-first companies to learn about their app users without invading their privacy. We predict the user behavior based on their context, demographics, mood, etc. in order to identify best timing for out-reach, without retrieving any data!

Our novel architecture speeds up the learning process by more than 50x, rendering it practical for real-world mobile set-ups, by running the whole ML process on thousands of mobile phones in a distributed fashion.

As part of this internship, you will:

  • Discover the benefits and limitations of federated learning and finding ways to overcome the latter;
  • Work on mobile sensor, activity, and app data to enable ML on disparate and skewed data sources;
  • Select and fine-tuning ML algorithms that are suitable for our application, with an efficient federated learning version, in Python or Java, and
  • Even building federated algorithms from scratch!

Latence Technologies

Real-time AI-based analytical decomposition of 5G network latency

LatenceTech offers a cloud analytics and monetization solution for cellular networks with a special focus on ultra-low latency connectivity. Using SAAS and AI, our solution helps mobile operators, telecom vendors and advanced industries to track, predict and secure the new benefits of 5G cellular technology.

The project consists in performing an analytical decomposition of the response time latency of 5G cellular technology. This will allow a better understanding of the reason for the high variance in milliseconds of the 5G latency by analyzing, in real time, the sub-components of the 5G latency such as transmission time, propagation time, routing time, etc. This data will allow customers (mobile operators) to take palliative and preventive measures to improve the quality of the 5G network in terms of latency. Understanding the components of latency will help to “understand why and how” the network generates such latency and why it varies over time.


Development of an AI model to facilitate data extraction from forms

At, we are changing the supply chain and logistics landscape by providing the industry with AI-assisted tools. We want to provide an unprecedented experience to our users with the latest technologies to better serve their customer.’s current value-add is to extract data from forms based on specific templates.  We also have a method to extract data without a template, but it lacks precision.

The project is therefore to create a generic template that can better extract data from a form into structured data. Using computer vision techniques, we will be able to identify the tabular data as well as the available key values.

As part of this internship, you will:

  • Analyze the current methods of the company in order to make a report;
  • Propose an alternative solution to the current method of information extraction;
  • Implement the solution in proof of concept mode;
  • Deploy the solution in the SaaS platform of



Accelerating an industrial digital twin using AI

Jumine‘s goal is to bring mines to their optimum for a more sustainable mining industry through digital solutions.

Jumine has a digital simulator of a semi-autogenous mill. It is based on physical principles. Its inputs are the process variables of mineral processing plants and its outputs are the behavior inside the mill, a crucial information, but impossible to measure directly. Operating this simulator in real time, in parallel with normal operation, allows mineral processing plants to achieve higher productivity.

As part of this internship, you will:

  • Conduct a literature review and describe the state of the art of decision tree algorithms;
  • Improve the decision tree algorithm already implemented in our software according to the new knowledge obtained during the literature review;
  • Improve the speed of the algorithm by making it GPU-enabled.

Reducing food waste through artificial intelligence

Olic ai offers food service providers (restaurants, grocery stores, bakeries) a demand prediction solution to optimize the production and supply of perishable products. Each year, food service providers produce the equivalent of $6.2 billion of food waste in Canada. OLICAI’s mission is to reduce food waste and its ecological impact on the planet. OLICAI’s demand prediction solution allows food service providers to optimize their production and supply of perishable products by providing them with a daily report of expected demand. OLICAI uses artificial intelligence to predict how much food will be sold each day, allowing customers to reduce both food waste and associated costs as well as increase profits by limiting stock-outs.

As part of this internship, you will:

  • Familiarize yourself with time series forecasting models and existing training and evaluation pipelines.
  • Explore and prototype new prediction methods using hierarchical forecasting and intermittent time series forecasting Data engineering and applied data science
  • Identify new sources of exploitable and relevant data
  • Conduct exploratory analysis of their relevance for demand forecasting
  • Develop a proof of concept of a pipeline to exploit the acquired data in a machine learning model.

Sport AI

Computer vision and natural language applied to soccer performance analysis

Sport AI uses artificial intelligence to analyze the performance of soccer teams in real time to help coaches make decisions and players improve.

The student will have the opportunity to work on one of the following two requirements: develop a computer vision model (supervised learning, OpenCV or TensorFlow framework) capable of detecting players and the ball on videos of soccer games in real time and develop a natural language recognition model (NLP, PyTorch framework) in order to label game events using voice commands. The detection model should be able to recognize players on the field and track them throughout the video. The NLP model should result in a model that can be integrated with our performance analysis platform (operator) to communicate with our database in real time.

Student profile

Although the program is open to all students enrolled in Campus Montréal institutions (Université de Montréal, Polytechnique Montréal, HEC Montréal), McGill University and Laval University who meet the eligibility criteria and demonstrate the abilities required for the project, the main academic programs from which the students will be drawn are as follows:

HEC Montréal

Polytechnique Montréal

Modular Master’s (or DESS) in Computer Engineering

 Université de Montréal

Université McGill

Université Laval


  • December 4, 2023 to midnight January 14, 2024: Call for internship projects from startups
  • January 15 to February 2, 2024: Projects selected and approved by partner universities
  • February 5 to 23, 2024: Publication of internship offers and interviews
  • February 9, 2024, 10am to 12pm: “IVADO Startup Day” student event. Come and discover the selected projects
  • February 26 to March 22, 2024: Finalization of internship agreements and submission of Mitacs applications
  • From May 2024: Start of internships.

*Please note that the internship start date is subject to Mitacs approval. We are not responsible for these delays.

Amounts, duration and terms of payment

The program is a 4-month full-time AI credited internship worth $15,000. Ten $15,000 scholarships will be awarded to student-interns1. Internships begin in May. The official start date is subject to approval by Mitacs. We are not responsible for these delays.

A contribution of $3750+tx (25% of the cost) is required from participating startups. This contribution will be invoiced by Mitacs and must be paid before the start of the internship. Any delay in payment of the contribution will delay the start of the internship.

IVADO also contributes an amount of $3750 (25% of the cost) and Mitacs completes with a contribution of $7500 (50% of the cost).

For more information on the Mitacs Business Strategy Internship program

1- For students in DIRO’s MSc in Computer Science (UdeM) and Mila’s MSc in Machine Learning, internships must be 6 months full-time. Two internship units are required, representing a cost of $8750+tx for the startup (the 2nd unit is $10,000, paid 50% by the startup). For the 6 months, DIRO students receive $25,000, while Mila MSc students receive $23,500, since $1,500 is retained to support internship supervision.

Eligibility criteria

For the student

  • Be enrolled in an Master program at one of our partner universities: Université de Montréal, Polytechnique Montréal, HEC Montréal, McGill University, Université Laval);
  • Register the internship as part of your course load (supervised project or credited internship);
  1. It is the student’s responsibility to take the administrative steps to register the internship in his or her academic program.
  • Submit an application following the home university’s standard process.

 For the startup

  • Have less than 20 employees;
  • Have a competent person to host the intern (the project does not rest on the shoulders of the intern);
  • Be part of or have completed a program with a recognized entrepreneurial support organization (accelerator or incubator) within the last three years;
  • Pay the invoice of $3750 + tx upon receipt to Mitacs before the start of the course.

Reminder: The internship will not be approved and cannot begin until the invoice has been paid. This is a determining factor in the realization of the internship and the start date. No exceptions are permitted.

Submitting an application

For the student

The list of available internships and information about each application process will be available in the “List of available internships” section below.

For the startup

Complete and submit this form before midnight January 14, 2024. Any submission that is incomplete or sent by any means other than the form will be automatically rejected.

We suggest that you copy and paste your text once written.

If you have any questions, please contact:

List of available internships

Coming up on February 5, 2024.

Evaluation of applications

A committee composed of :

  • Two to three IVADO technology transfer advisors, including the entrepreneurship advisor,
  • the Equity, Diversity and Inclusion (EDI) Advisor

The committee will assess the applications and make a selection based primarily on compliance with eligibility criteria, the quality of the proposed internship project and the project’s impact on the company. The evaluation committee will be multidisciplinary and in line with EDI principles.

The IVADO entrepreneurship advisor will present the selected internship projects to the partner universities, who will judge which proposals meet the requirements of their programs and can be presented to their students.

As for the choice of interns, it’s the startup’s responsibility to interview and confirm the successful candidate to the entrepreneurship advisor before the date they’ll be given.

Note on intellectual property

As this is not a research internship, all intellectual property belongs and remains with the startup. A confidentiality agreement (NDA) may be signed between the intern and the company.As this is not a research internship, all intellectual property belongs and remains with the startup. A confidentiality agreement (NDA) may be signed between the intern and the company.


For interns

Demonstrate integrity and respect in all aspects of your collaboration with the startup;

Respect the terms of the internship and ensure that objectives and deliverables are met to the best of your ability;

Mention IVADO in public communications about the internship and participate, whenever possible, in IVADO student activities.

For the startup company

Respect EDI principles when selecting candidates, in accordance with the IVADO EDI reference framework;

Consult the IVADO brochure on unconscious bias in recruitment;

Provide a working environment and infrastructure that enables the smooth running and completion of the project;

Demonstrate integrity and respect in all aspects of your collaboration with the intern;

Be available on February 9, from 10 a.m. to 12 p.m., for the presentation of internship projects to the student community;

Be available during the process leading up to the submission of the Mitacs application (a few meetings and e-mail exchanges are to be expected);

Complete the short feedback survey sent by IVADO at the end of the course;

Mention IVADO in public communications related to the intern’s work.

IVADO’s commitment to equity, diversity and inclusion

To ensure that all members of society benefit equally from the advancement of knowledge and opportunities, IVADO promotes the principles of equity, diversity and inclusion in all its programs. IVADO is committed to providing a recruitment process and research framework that are inclusive, non-discriminatory, open and transparent.