SEMLA Undergraduate AI Research Internship: Historical Reference for a Fully Funded Four-Month Call

SEMLA Undergraduate AI Research Internship: Historical Reference for a Fully Funded Four-Month Call

Historical status

This page is an archive entry, not a current open-call notice. SEMLA Research Center announced an undergraduate AI research internship and invited students to apply, but the verified announcement did not publish a fixed closing date. The official SEMLA website now exposes its general organization pages and an older residency-program page; it does not announce a new undergraduate cycle. The rolling deadline value records the absence of a published cutoff in the archived call. It does not mean that SEMLA is accepting applications today. Check the official SEMLA site before preparing a submission.

The official program source is now hosted on the SEMLA domain at semla.quebec. The relevant public program page is the SEMLA Residency Program. The original semla.ca address in the older record could not be verified and is not used as the current external URL.

What the archived call offered

The SEMLA Research Center announcement described a fully funded, four-month research experience for undergraduate students registered at Canadian universities. Its purpose was to help a student move from undergraduate study toward research work and graduate-level preparation. That is more specific than a general software internship: the call placed students in a research environment and described work alongside graduate students and researchers.

The announcement named three practical areas of work:

1. Fundamental AI research with SEMLA research labs, graduate students, and researchers.
2. Engineering AI projects in collaboration with an industrial partner.
3. Contributions to open-source AI tools maintained by SEMLA labs and used by the community.

It also described the expected value of the experience as exposure to experiments and publications, hands-on engineering and scientific problem solving, advanced AI skills, and mentoring from professors and research teams in Québec and Canada. These are the terms that can be attributed to the archived announcement. A specific supervisor, lab, project, work location, start date, or publication outcome was not identified there.

At a glance

Who SEMLA is

SEMLA stands for Software Engineering for Machine Learning Applications. Its official site describes work on complex intelligent software systems and presents activities in software engineering, machine learning, training, research, conferences, and collaborations. The Join page says SEMLA brings together software engineering researchers from Québec and Canada to develop methods, tools, and technologies for secure, reliable, and trustworthy intelligent applications.

That context matters when evaluating the internship. A student should expect the program to sit at the intersection of machine learning and the engineering needed to make intelligent software work in practice. The archived undergraduate announcement used broad AI language, but it also pointed to research labs, industrial collaboration, and open-source tools. Those details suggest a mixed research-and-engineering experience rather than a narrow course or a short coding exercise.

Funding: what is and is not confirmed

The undergraduate announcement called the opportunity fully funded. It did not state a dollar amount, payment schedule, currency, travel allowance, housing support, or whether funding was provided as a stipend, employment income, or through a partner program. Those terms should not be inferred from the word “funded.” A student considering relocation or an unpaid leave from another role would need written confirmation from SEMLA before making financial plans.

SEMLA’s public Residency Program page contains a separate, older program description. That page says its Summer 2023 internships paid 6,000 CAD for 15 weeks and followed the Mitacs Globalink Research Award inbound model. It also describes a structured research bootcamp. Those are useful evidence about an earlier SEMLA residency model, but they are not confirmed financial terms for the archived undergraduate call described here. The two records should not be combined into a new claim that the undergraduate internship paid 6,000 CAD or followed the same funding mechanism.

Eligibility

The archived undergraduate announcement identifies one clear eligibility condition: the applicant must be an undergraduate student registered at a Canadian university. It also presents the intended applicant as curious, driven, already experimenting with AI, and ready to explore AI research. The wording does not establish a required citizenship, permanent-resident status, province, institution, major, GPA, year of study, language score, or prerequisite course list.

That means an applicant should separate confirmed eligibility from sensible preparation. Being enrolled as an undergraduate at a Canadian university is the core published requirement. Experience with Python, machine learning, data work, software projects, or research reading may help a student demonstrate readiness, but the verified call does not set a formal technical checklist. Likewise, the call does not say that only computer science students may apply. Students in another field should not assume they are excluded, but they should be ready to explain the connection between their background and the research they want to pursue.

Before treating any future SEMLA announcement as a continuation of this call, verify whether the eligibility wording changes. A later cycle could narrow the universities, require a particular year of study, use a partner-based nomination process, or invite graduate students as well as undergraduates. The older Residency Program page, for example, discusses international students connected to Mitacs network countries and also mentions graduate students. That is evidence about that residency page, not a standing rule for every SEMLA opportunity.

What the work could involve

The work described by the archived announcement has three connected layers. First, a student could participate in fundamental AI research with people already working in a SEMLA lab. That may involve reading research papers, defining a tractable question, implementing an experiment, inspecting results, and discussing limitations. The source promises exposure to experiments and publications, but it does not promise that every intern will become an author or publish a paper.

Second, the call mentions an AI engineering project with an industrial partner. This signals that some projects may be shaped by a practical problem and may require attention to software quality, data handling, reproducibility, evaluation, or communication with people outside the lab. The source does not name the partners or guarantee that every intern will work directly with an external company.

Third, the program includes contributions to open-source AI tools maintained by SEMLA labs and used by the community. This could mean code, tests, documentation, examples, issue investigation, or other project work, depending on the lab. The announcement does not specify a repository, programming language, contribution volume, or release process.

These three elements make the program attractive to students who want to see how research ideas become working artifacts. They also mean the experience may include uncertain results, revision, and technical communication. Someone looking only for a predictable feature-development internship may want to compare this with a conventional industry placement.

Application guidance for the archived call

The official announcement used an “Apply now” instruction and linked to an application form. It did not publish a detailed checklist in the announcement itself. The safest reconstruction of the application path is therefore limited:

1. Start from SEMLA’s official domain and confirm that a current call exists.
2. Open the application link provided by SEMLA rather than relying on a copied form URL from a third-party listing.
3. Read the current form’s eligibility and document instructions before preparing files.
4. Submit the requested information through the official form, keeping a copy of the submitted materials and confirmation.
5. Contact SEMLA through its current official contact route if the form is closed, the funding terms are unclear, or no acknowledgement arrives.

For the archived call, a focused preparation package would reasonably include a concise CV, a short statement explaining the applicant’s interest in AI research, and links to credible technical or research projects. These are preparation recommendations, not a verified list of mandatory documents. Do not claim that a transcript, reference letter, portfolio, GPA threshold, interview, or statement length is required unless a future official form says so.

How to prepare a credible application

A strong statement would connect one concrete experience to one research question. For example, a student might describe an experiment whose results were weaker than expected, explain how they diagnosed the problem, and identify what they would test next. That gives a supervisor evidence of curiosity and persistence without overstating expertise.

The CV should make technical work inspectable. Name the project, state the student’s contribution, identify the data or software used, and give one measurable result when possible. A small, well-understood experiment is more useful than a long list of tools the applicant has only tried once. If a project is on GitHub, make the README clear and remove credentials, broken links, and unexplained generated files.

Applicants should also be ready to discuss how they learn. Research supervision often involves unfamiliar papers, incomplete specifications, and feedback that changes the direction of a project. The archived call does not promise a particular project match, so flexibility is important. The best preparation is not to pretend to know every AI method; it is to show that the applicant can define a question, test an idea, communicate results, and revise their approach.

Questions to confirm before any future application

Because the archived call left several operational details open, applicants should ask SEMLA to confirm:

• Whether a new undergraduate cycle is open and which application form is active.
• The exact funding amount, payment schedule, and any conditions attached to “fully funded.”
• The expected start period, weekly commitment, and whether the work is remote, hybrid, or in person.
• Whether the applicant must be enrolled for the full internship and whether final-year students are eligible.
• How students are matched to labs, supervisors, industrial projects, and open-source work.
• Which documents are mandatory and whether references or transcripts are requested.
• Whether the internship is connected to Mitacs or another funding partner.
• What deliverables are expected at the end of four months.

These questions are especially important because the current SEMLA public pages include an older residency format with different duration and funding language. A student should never use the older 6,000 CAD or 15-week terms as a substitute for current confirmation.

Bottom line

The archived SEMLA undergraduate call was a specific research opportunity: fully funded, four months long, open to undergraduates registered at Canadian universities, and oriented toward lab research, industrial collaboration, and open-source AI work. The verified official material does not provide a fixed deadline or an exact amount for that undergraduate call. The current SEMLA domain is the authoritative place to check for a replacement cycle, but no new undergraduate cycle is announced on the public pages verified for this update.

Treat this page as background for understanding the opportunity, not as permission to submit an old form or as evidence that applications are open. If SEMLA publishes another call, replace this archive entry’s status, deadline, funding, eligibility, and application instructions from that new official source.