Video presentation

Target group

The IVADO “Scientist in Action” program is aimed at startups interested in hosting a master’s-level intern to advance an applied research 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.

Objectives

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 employee.

Supported fields and examples of mandates

This program is designed to support research in the areas delineated in our CFREF funding proposal: data science in the broad sense, encompassing methodological research in data science (machine learning, operations research, statistics) and its applications in multiple sectors, including our priority sectors (health, transportation and logistics, energy, business, and finance) and any other sector of application (e.g., sociology, physics, linguistics, engineering).

Any project pertaining to data valorization, e.g., in:

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

Without limitation, internship projects may focus on the following:

  • Contribution to the improvement of processes involved in data collection and data quality;
  • Implementation of measures for monitoring performance indicators (KPIs);
  • Creation of modern, practical and efficient visualization tools (Power BI: dashboards, reports);
  • Improvements to existing BI reports and dashboards;
  • Harnessing of available data to meet business needs;
  • Development and execution of database queries (SQL);
  • Ensuring data integrity, including extraction, storage and processing;
  • Understanding of the needs of a business and users so as to provide them with appropriate data solutions;
  • Assessment of opportunities for use of artificial intelligence;
  • Design of tools and models to serve as a basis for decision-making;
  • Formulation of forecasting models in a business context (e.g., purchasing, sales, cancellations, unsubscribe requests, outages);
  • Customer segmentation in a marketing context;
  • Optimization of inventory management;
  • Modelling of credit risk;
  • Analysis of unstructured data (text) in a sentiment analysis context;
  • Etc.

Student profile

Calendar

  • November 21, 2022 to January 8, 2023 at midnight: call for internship projects from startups
  • Week of January 9, 2023: analysis and selection of the selected projects, communication with the selected startups
  • January 9 to 23, 2023: Validation and writing of internship offers
  • January 23 to February 10, 2023: publication of internship offers
  • May 2023: start of internships – Please note that the start date of internships is subject to approval by Mitacs. We are not responsible for these delays.

Amounts, duration and terms of payment

This is a 4-month, full-time AI applied research internship program, starting no earlier than May 1, 2023. The official start date of the internship is contingent upon approval by Mitacs. We are not responsible for these delays. For more information, visit Mitacs Acceleration program.

Ten $15,000 scholarships will be awarded to student interns.

*Some programs retain a portion of the award for research expenses.

A 25% contribution (i.e. $3750+tx) is required from participating startups. This contribution will be invoiced by Mitacs and must be paid before the start of the internship. IVADO also contributes 25% (i.e. $3750+tx) and Mitacs completes with a contribution of 50% (i.e. $7500).

*In the case of students at the MSc in Mila, the contribution of the startup is double since 2 units are required.

Eligibility criteria

For the applicant

  • Be enrolled in an MSc program at one of the Campus Montréal universities (Université de Montréal, Polytechnique Montréal, HEC Montréal);
  • Register the internship as part of their course load (supervised project or credited internship); NB. It is the student’s responsibility to take the administrative steps to register the internship in his/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 or have completed a program of a recognized coaching organization
  • Pay a contribution of $3750 to IVADO before the beginning of the internship

Submitting an application

For the applicant

The list of available internships and the information pertaining to each application process will be available below.

For the startup

Complete and submit the form before midnight on January 8, 2023. Submissions that are 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 the consultant: melissa.authier@ivado.ca

List of available internships

2023 Edition:

1. Soralink

Predictive maintenance with AI

Soralink provides a complete predictive maintenance solution using AI for critical equipment in manufacturing sectors.

The main task is to help train, deploy and test the AI models we have for anomaly detection for the time series data we collect from our sensors.

 Objectives: 

  • Increase the accuracy of anomaly detection; 
  • to be able to differentiate different types of failures from these signals.

This internship is available for students from:

  • Polytechnique: for more information, see La Ruche
  • UdeM: for more information, see StudiUM
  • HEC: for more information, see My Career Portal – offer no. 60657

2. Jumine

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.

Objectives:

  • Conduct a literature review and describe the state of the art of decision tree algorithms.
  • To 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.

This internship is available for students of:

  • Polytechnique: for more information, see La Ruche
  • UdeM: for more information, see StudiUM
  • HEC: for more information, see My Career Portal – offer no. 60663

3. Quote n Go

Revolutionizing home maintenance with AI to detect and measure areas of interest in satellite imagery

Quote n Go allows homeowners to get quotes for exterior home maintenance services automatically in just seconds. Simply enter your address, select the service you want and voila! Homeowners can, from a web platform, easily order their exterior maintenance services and then, the work will be executed by a verified contractor in their area. Thanks to its artificial intelligence algorithms, Quote-n-Go is able, from a satellite image of a client’s house, to measure the exterior surfaces to be maintained in order to offer a quote in real time, thus saving precious time for both the owner and the contractor who will perform the maintenance work.

The main objective of this internship is to improve Quote-n-Go’s core technology in order to better measure the surfaces currently detected on a satellite image and to measure a wider variety of surfaces. To do this, you will explore different types of semi-supervised and unsupervised models to take advantage of the amount of satellite imagery available and state-of-the-art computer vision methods. Throughout the internship, you will have the chance to work with modern tools such as PyTorch, OpenCV, AWS SageMaker and Jupyter Notebook. Your mission will essentially consist of a Research and Development effort that will allow you to greatly deepen your technical knowledge in AI while contributing to the technological advancement of a startup wishing to revolutionize the property maintenance industry.

This internship is available for students from:

  • Polytechnique: for more information, see La Ruche
  • UdeM: for more information, see StudiUM

4. Lerna AI

Building a privacy-preserving federated recommender system for mobile devices

Lerna AI helps app developers better understand their users and optimize their campaigns. Traditionally, apps have relied heavily on third-party trackers and data. Due to privacy laws and blockers, this is no longer possible. Lerna AI’s Android library allows app publishers to gather real-time behavioral insights and predictions based on enriched third-party data that never leaves the device, without having to rely on expensive third-party data. This is made possible through the use of state-of-the-art privacy-preserving federated learning. This predictive capability allows app publishers to increase revenue, extend app usage time and reduce churn.

Objectives: 

  • Explore work in the literature on collaborative filtering and federated/differentially private logistic regression for recommender systems. 
  • Implement the above two methods in Kotlin.
  • Test the prediction accuracy of both methods on public datasets and integrate the best method into our system.

This internship is available for students from:

  • Polytechnique: for more information, see La Ruche
  • UdeM: for more information, see StudiUM
  • HEC: for more information, see My Career Portal – offer no. 60658

5. Top Gun Formation

Compliance software for financial services with automotive dealerships

Top Gun Formation is a young company that works in financial services dedicated to automotive dealers and manufacturers (Chrysler, GM, Kia, Hyundai), and collaborates with several financial services providers dedicated to the automotive sector (iA, SSQ, LGM). We want to put our expertise in financial services dedicated to dealerships to work to help our clients simplify their operations with respect to compliance and respect for the laws and standards in force (AMF, OPC, banking standards compliance) while respecting data ethics. 

With your help, the Top Gun team will succeed in restoring the financial services industry to its rightful place as a pleasant, pressure-free, transparent and legally compliant customer experience. The student will be driven to improve Top Gun Formation’s core technology to better perceive business intelligence for its various automotive dealership clients. 

Objectives:

  • Contribute to the improvement of processes related to data collection and quality; 
  • Implement measures to monitor performance indicators (KPI); 
  • Create and improve modern, practical and efficient visualization tools (Power BI: dashboards, reports); 
  • Evaluate trends and formulate forecasting models in a business and socio-economic context to be targeted (seasonality, type of financing, average salary by region). 
  • Evaluate opportunities to use artificial intelligence in the 3rd phase of implementation of our compliance management software.

This internship is available for students from:

6. Olic ai

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. 

Objectives:

  • familiarization 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 
  • 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.

This internship is available for students from:

  • Polytechnique: for more information, see La Ruche
  • UdeM: for more information, see StudiUM
  • HEC: for more information, see My Career Portal – offer no. 60660

7. Sport AI

Computer vision and natural language applied to soccer performance analysis

Sport AI use 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. 

This internship is available for students from:

  • Polytechnique: for more information, see La Ruche
  • UdeM: for more information, see StudiUM
  • HEC: for more information, see My Career Portal  – offer no.60651

8. Azimut Medical

Design of an LSTM algorithm for unstable walking in the elderly

Azimut Medical is a Montreal-based company specializing in the development of intelligent inflatable protective garments specifically adapted to the prevention of hip fractures in the elderly. Azimut Medical’s mission is to preserve the dignity and promote the independence of seniors by eliminating the morbidity associated with such injuries. Each year, more than 330,000 seniors suffer a hip fracture in North America alone. In Canada specifically, falls are the most significant cause of injury to seniors. These fractures cost the health care system over $20 billion and cause over 70,000 deaths annually in North America. Half of those affected will lose the ability to walk within a year permanently, resulting in a major impact on their quality of life. The Air-Sequr belt is an innovative inflatable garment that absorbs the impact of a fall at the hip level. 

The overall objective of this internship is the design of a deep learning Long Term Short Term Memory (LSTM) algorithm to detect unstable walking in an elderly person. 

Objectives: 

  • Transform data to extract the most studied gait metadata in the literature (root mean square of signals, standard deviation of signals, time during the stance phase of gait, time during the swing phase of gait, gait speed, etc.). 
  • Investigate the relevance of the metadata by principal component analysis (PCA). 
  • Feeding the LSTM algorithm.
  • Evaluation of the sensitivity and F1 with test data.

At the end of this internship, the intern will have designed an LSTM algorithm to detect an unstable walk; an innovative algorithm in the research field. 

This internship is available for students from:

  • Polytechnique: for more information, see La Ruche
  • UdeM: for more information, see StudiUM

9. Code F

NLP application for financial self-coaching

Code F Financial health is a social economy enterprise whose objectives are to educate, accompany and financially equip citizens through financial coaching services, financial education workshops and various guides to help them manage their money. The internship will consist of using NLP and/or NLU techniques and motivational psychology to hold a conversation and offer coaching, while being able to discern the user’s state of mind and using a tone/personality that matches the user’s profile and needs. This while being able to encourage/motivate, offer support to users in achieving their efforts and adopting healthy money management habits.

This internship is available for students from:

  • Polytechnique: for more information, see La Ruche

10. Applicare AI

Development of predictive models using physiological and behavioral parameters for patient triage in all disaster situations (VIMY Multi-system)

Applicare AI is a medical technology startup founded in 2022, which develops predictive models for the risk of complications in high-risk individuals using artificial intelligence algorithms applied to data collected continuously via continuous monitoring medical devices.

This internship is part of the research program, VIMY, a field-deployable multi-system intensive care unit capable of managing multiple casualties. It is based on an artificial intelligence capability consisting primarily of sensors, data acquisition systems, automated interactive systems, and algorithms that assist in the decision-making process. Since it is designed for any disaster situation, including a Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) event, VIMY will significantly reduce the burden on the clinician and enable a more robust medical response.

Objectives: 

  • Feed the electronic casualty card system with vital sign data from public databases in real time-second accuracy (extract, store and process vital sign data such as respiratory rate, systolic and diastolic pressures, heart rate, SpO2, Temperature, neurological status, etc…), and improve the existing dashboard. 
  • Develop and validate predictive models for patient triage (STAT, Urgent, Non-urgent, Stable) based on the NEWS-2 scoring system 

This internship is available for students from:

  • Polytechnique: for more information, see La Ruche
  • UdeM: for more information, see StudiUM
  • HEC: for more information, see My Career Portal – offer no. 60665

Evaluation of applications

For evaluation of the applied research internship project applications submitted by the startups, a committee comprising the three MSc internship academic representatives of Campus Montréal (Université de Montréal, Polytechnique Montréal, HEC Montréal), a representative of the entrepreneurship support organizations ecosystem and the IVADO Entrepreneurship Advisor will be formed. Compliance with the eligibility criteria, the quality of the proposed internship project and the project’s impact on the company will be the main criteria evaluated.

If there is more than one applicant interested in a project, an interview will be arranged with the company, which will make the final choice.

Note regarding intellectual property

All intellectual property belongs to the startup. A non-disclosure agreement (NDA) may be signed by the successful applicant and the company.

Commitments

  • Applicants
    • Show integrity and respect in all exchanges with the startup;
    • Mention IVADO in all public communications about the internship (e.g., postings on social platforms) and take part, when possible, in its various student activities.
  • Startup
    • Provide a work environment conducive to completion of the project;
    • Show integrity and respect in all exchanges with the student;
    • Mention IVADO in public communications relating to the intern’s work.
  • Our commitment to equity, diversity and inclusion
    • To ensure all members of society draw equal benefit from the advancement of knowledge and opportunities in digital intelligence, we promote principles of equity, diversity and inclusion across all of our programs, and we commit to providing a recruitment process and research setting that are inclusive, non-discriminatory, open, and transparent.