Mitacs Accelerate Proposals
The Mitacs Accelerate program is a common funding method for DeepSense projects. This guide will help you through the process of writing a funding proposal for submission to Mitacs.
Mitacs and a company each pay for half of the project. Mitacs funding is allocated in *units* of 4-6 months with each unit paying $15000 to the student.
See the Mitacs web site for the proposal template and guide.
- 1 Planning Meeting
- 2 General advice
- 3 First Steps
- 4 Project Detail
- 5 Timeline
- 6 Basic Information
- 7 Company information
- 8 Remaining steps
- 9 Scientific Committee Review
- 10 Signatures
- 11 Review Process
As with any project, the first step is to have a planning meeting with the student, company, supervisor, and possibly with a DeepSense staff member. If you are reading this guide you probably already had at least one meeting with the company but there are a few items you need to be clear on. If necessary, have another meeting or discuss these items by email or phone with your supervisor, DeepSense staff, and/or the company:
- Number of students and duration of the project
- Overall goal of the project
- A general idea of how to approach the project and belief it is feasible
- There are a lot of sections in the proposal so write the proposal in stages instead of trying to do it all at once or in order.
- Be iterative: write an outline of what you intend to do, expand the outline to sentences and paragraphs, and then edit for clarity and content.
- Get feedback often. Involve your supervisor, other students on the project or related projects, and DeepSense staff. It will take several rounds of feedback and editing to write a strong proposal.
- Be mindful of both the science and the benefit to the company. A DeepSense project is a mix of both. There needs to be specified deliverables for the company and an explanation of how those deliverables solve a problem for the company. There also needs to be a research question to solve or novel advance that doesn't currently exist. This can range from applying a known state of the art technique to a novel dataset or situation all the way to developing a brand new solution.
- Use topic sentences and strong closing sentences. A topic sentence is a sentence that explains the purpose of a paragraph and is typically at the beginning of the paragraph. In most cases you should be able to read just the first sentence of each paragraph and still understand the main ideas. A strong closing sentence, especially at the end of each section, will encourage the reader
- Ask your supervisor or DeepSense staff if you can see an example of a successfully funded Mitacs proposal. This will help you understand the scope and detail required in each section.
The first steps are to do some research and write down the general idea of the project
2.1 and 7.1: Title
Write down a draft title. You may want to change this later on so don't worry too much about writing a catchy title yet.
Approximately 200 words. The abstract summarizes the entire project. Write out the problem to be solved, why it is important, the current state of the art and why that is insufficient, your proposed solution, and finally the steps and deliverables of the project.
The abstract is important but does not need to be polished at this stage. Just write out each of these facets and if you can't then you need to do some research or discuss the project further with your supervisor, the company, and/or DeepSense staff.
Minimum 500 words. This is where you explain the current state of the problem in detail and cite relevant research.
First give a general overview of the problem and the broad research area. Cite some relevant survey papers or important guiding works.
Then summarize some of the more specific topics and research papers. Typically you will find papers that partially but do not completely solve your problem. Summarize their results as well as their pros and cons. It should be clear why you have selected these specific results and how this knowledge will contribute to completing the project.
Finally, explain how some of these results together can be used to solve your specific problem. For example, you may be using a deep learning model from one paper, adding a technique from a second paper, and then using a type of analysis from a third paper. Moreover, highlight any gaps that the current literature can't solve for your problem. It is important to explain how these methods fit together and show that your project is novel research.
Put your references in this section. Mitacs does not specify a reference format so use any consistent format. We've had good success with the APA format.
This section is just as important as it is in a scientific paper so be sure to check your reference details and order them consistently.
Now that you have a general idea of the project and have done some research it's time to get more specific with the deliverables and methods. Consider getting feedback on the sections you have already completed while you start on the next sections.
2.4 General Objective
Write out the main objective of the project. Split this up into sub-objectives. Very briefly summarize any information needed to explain a sub-objective such as how it will be tested or what data will be used.
2.5 Details of internships or subprojects
Although numbered like a regular section, each subsection of Details requires a significant explanation and should be treated as a full section in its own right. We'll complete some of these now but go back and do the other later.
For a very large project funded by a single mitacs submission you may need to break the project up into different subprojects. If so then the student(s) working on each subproject should fill out their subprojects information.
2.5.a Name of Intern
Write out the name of the student or students working on a shared goal.
2.5.b Specific Objectives
Write out the specific objectives that each student listed will work on. These should be matched with the general objective and sub-objectives as well as explaining what each individual student will do.
In this section you write out in detail how you will accomplish this project.
This is the meat of the proposal and must includes the datasets, tools, and methods you will use in enough detail for an expert external reviewer to determine if the project is feasible and will accomplish your objectives. Consider this like the methods section of a scientific paper.
Explain the analysis you will complete and how you will show that you have met each sub-objective.
Explain the deliverables of the project such as software, reports, publications, etc. What will the project create and how will it meet the sub-objectives?
2.5.f Benefit to the intern
Explain what you will gain from this project. Examples include:
- exposure to an ocean company and/or novel data
- learning a new analysis method
- opportunity to contribute to an industry problem or a solution that will be used by the partner to do X
- opportunity to publish in peer-reviewed venues and/or write a thesis
Now that you have a good idea of the specifics of the project it's time to plan. Revise and edit the previous sections and seek feedback.
Then, take the steps your propose to do in your methodology and create a *gannt chart* showing how long each of those steps will take:
First, list out the major steps of the project, goals, and deliverables such as:
- obtain data
- preprocess the data
- design the machine learning model
- train the model
- test the model
- improve the model
- train and test again
- write a report
Then think about how long each step of the project will take in weeks, half months, or (for a long project) months. Break the project up into 4 month sections and create a gannt chart for each. You will probably want to do this in a spreadsheet program such as Excel for easy editing and then copy the chart into the mitacs proposal later.
There are some informational sections you need to complete. You will need to obtain some information from your supervisor:
- 2.8 Relationship (if any) to past/other Mitacs projects:
- 3 Declarations
- 4.1 Lead academic supervisor in Canada
- 4.3 Interns
- 4.4 Interns to be determined (TBD)
When your proposal is nearly ready you will need to send it to your partner company for their feedback. Do this in conjunction with your supervisor and/or DeepSense staff.
Be sure you make it clear to the company that *Section 7.2 Public project overview* will be publicly available on the Mitacs web site. They must review this section carefully.
Section of the proposal that should be completed by or with the help of the partner organization are:
- 2.5.g Partner interaction
- 2.6 Relevance to the partner organization and to Canada
- 4.2 Partner organization in Canada
- 7.2 Public project overview
There are a few other sections that must be completed
5 Budget and invoicing
Your supervisor or DeepSense staff can help with the budget
6 Suggested reviewers
You need to suggest 6 reviewers. They cannot be from your university and you cannot have published with them or have plans to collaborate with them in the near future.
Moreover, each reviewer must be from a different university or organization than the others.
We recommend selecting subject experts that are knowledgeable of the research area but also likely to be generally favourable of the research and provide constructive criticism and suggestions. Contact your supervisor and/or DeepSense staff if you need help selecting reviewers.
Scientific Committee Review
The proposal must be reviewed by the DeepSense scientific committee.
After the scientific committee has approved the project and the company has agreed and signed the necessary sections, you and your supervisor will need to sign:
- 7.3 Signatures
- Appendix A - Intern consent form
- The separate mitacs IP agreement
Proposal review will take approximately 4-8 weeks so it is important to submit the proposal early before the start of a project. Most well-written proposals are funded but you may need to provide extra information to address reviewer comments.