Looking for meaningful summer work that gets you out of the classroom and into the field?

The Fishery Officer Student Program (FOSP) offers post-secondary students a paid opportunity to gain hands-on experience with Fisheries and Oceans Canada (DFO) while supporting the conservation and protection of Canada’s fisheries and aquatic ecosystems.

Work alongside experienced fishery officers, learn how conservation and enforcement operations support communities across Canada, and build practical skills for a future career in the federal public service.

DFO is seeking curious, motivated students from diverse backgrounds who are eager to learn and make a difference.

What you will do

Students will support Fishery Officers by:

• Participating in public education and outreach activities;

• Accompanying Fishery Officers on their routine patrols;

• Assisting with the management of fisheries-related materials and maintaining inventories;

• Responding to public inquiries and document preparation;

• Preparing and maintaining vehicles, vessels and equipment; and 

• Performing general office administration and organizational duties.

What we are looking for

We are seeking full-time post-secondary students who meet FSWEP eligibility criteria to join the Fishery Officer Student Program.

Candidates must be available to work full-time from May 3, 2027 through the end of August 2027.

Preference will be given to Canadian citizens and permanent residents, with the exception of a job located:

• in Nunavut, where Nunavut Inuit will be appointed first; and/or

• in Yukon, qualified members of the Yukon First Nations will be appointed first, followed by qualified Indigenous persons.

The ideal candidate is:

✔ Reliable, calm, and able to exercise sound judgment;
✔ Motivated, hardworking, and eager to learn;
✔ Flexible and comfortable working in both office and field environments;
✔ A strong communicator with the ability to communicate in English and/or French, depending on the work location;
✔ Interested in the marine environment and supporting fishery officers.

Fields of Study

Students from a variety of disciplines are encouraged to apply. Relevant fields of study may include, but are not limited to:

• Environmental or natural resource management
• Marine or aquatic sciences
• Fisheries management
• Law enforcement, criminology, or public safety

This is a unique opportunity to gain practical experience while contributing to real-world conservation and protection efforts.

Conditions of employment

This work may involve field, outdoor and operational environments, students must meet the following conditions of employment:

Security Requirement: Various depending on the work locations (Enhanced Reliability or Enhanced Secret). For more information, please visit the following website: security screening process.

Driver’s Licence: Possess and maintain a valid Canadian driver’s licence that authorizes you to operate a motor vehicle independently in Canada.

Age Requirement: Must be at least 18 years old at the time of the employment.

Physical Condition

• Students must be physically capable of safely lifting and carrying items weighing between 10 kg and 20 kg on a regular basis.

• Students must be physically fit and be able to spend significant periods standing, walking, hiking or working on vessels.

Willingness to work irregular hours and overtime

• Must be willing and able to work:

  • Shift work;

  • Weekends and holidays;

  • Extended hours when operationally required; and

  • Overtime on short notice when operationally required.

Field and outdoor work

• Must be willing and able to work:

  • Outdoors;

  • On, in and near water;

  • In remote and/or coastal locations; and

  • In all weather conditions.

Travel and deployment

• Must be willing and able to travel for work and accept assignments based on operational needs, if required.

*Note: Travel required for operational purposes will be arranged and/or reimbursed in accordance with Government of Canada travel directives and departmental policies.

Additional requirements

• Housing or relocation assistance will not be provided for this position. Students are responsible for securing their own accommodations and covering any costs associated with relocating to the selected work location. 

• Students can expect to receive communications within one week of the closing date.

• It is your responsibility to regularly monitor your email account, including your junk/spam folders, for communications related to this selection process, and to notify us of any changes to your mailing address, telephone number, or email address by contacting DFO.NATCPFOSP-PEAPCPNAT.MPO@dfo-mpo.gc.ca.

• Following the closing date, you will receive an email invitation to complete your candidate profile in the VidCruiter platform. Completion of this profile is mandatory in order to be considered further in the staffing process. Students who do not complete this step within the specified timeframe will not be considered for this job opportunity.

Students will be asked to rank their preferred work locations when completing their candidate profile in VidCruiter.

More details: https://emploisfp-psjobs.cfp-psc.gc.ca/srs-sre/page01.html?poster=2022&lang=en

What you will do

Students work in teams with DFO staff to collect, process and analyze data, provide operational support, and report on fisheries related operations. Generally, students are engaged in field and lab work, but may also do office work. 

Typical tasks may include:

•  collecting biological samples/information from candidate lakes and rivers

•  sampling water, sediment, benthic invertebrates, zooplankton, freshwater mussels, and fishes

•  assessing the chemical, physical and biological nature of Great Lakes tributaries for sea lamprey management

•  collecting habitat and species information to assess the status of Federal Species at Risk and of Aquatic Invasive Species under the Species at Risk Act (SARA)

Note 1: While working in the field, you may encounter adverse weather conditions and travel for extended periods of time to complete the research project. You may also end up working shift work or extended hours, both of which receive compensation.

Duration: Full-time from April 26, 2027 to September 3, 2027

Note 2: There is limited flexibility in contract dates, especially for the start date, due to the extensive mandatory training schedule at the beginning of all new student contracts, and the schedule of field research activities through summer season.

What we are looking for

Students who are currently registered in a program of study at a post-secondary institution who have taken or will be taking aquatic biology courses.

We are looking for students who have:

• a curious mind 

• initiative 

• teamwork skills 

• good communication skills 

You must meet the FSWEP eligibility criteria.

Language: English

Preference will be given to Canadian citizens and permanent residents.

Note 3: This program is administered from Burlington, Ontario. However, more than half of the positions are located in Sault Ste. Marie, Ontario. If you are invited to an interview, you will have the opportunity to choose between being based out of Sault Ste. Marie or Burlington.

*You do not need to apply if you were previously employed under this program. If you would like to be considered for current job opportunities, please contact DFO.OPStudent-EtudiantOP.MPO@dfo-mpo.gc.ca.

Conditions of employment

Conditions of employment are requirements that must be met or complied with before being hired to a particular position and must be maintained throughout the duration of employment.

•  Complete and meet the standards of a Health Canada Medical exam (will be coordinated by DFO) which includes a:

• hearing test

• physical examination

• electrocardiogram

• colour-vision examination

•  Obtain a government-issued reliability security clearance

•  Be willing and able to travel to, and work in, the United States; therefore, some positions may require a U.S. work visa.

At the time of interview, candidates must provide the following valid documents:

•  a valid driver’s licence, minimum Ontario G2 or equivalent from other jurisdictions

•  a Pleasure Craft Operators Card

More details: https://emploisfp-psjobs.cfp-psc.gc.ca/srs-sre/page01.html?poster=2042&lang=en

In this one-hour session, we'll show how ORCID iDs link researchers to their data in the CIOOS catalogue, why persistent identifiers matter for attribution and discoverability, and the simple steps to register an ORCID and associate it with your work. Whether you already have an ORCID or have never set one up, you'll leave knowing how to make your ocean data count toward your scholarly record. Bring your questions for the live Q&A.

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Chaque jeu de données océaniques que vous recueillez représente un travail bien réel — mais vous est-il vraiment attribué? 

Au cours de cette séance d'une heure, nous montrerons comment les identifiants ORCID relient les chercheuses et chercheurs à leurs données dans le catalogue du SIOOC, pourquoi les identifiants pérennes sont importants pour l'attribution et la découvrabilité, ainsi que les étapes simples pour créer un identifiant ORCID et l'associer à vos travaux. Que vous ayez déjà un identifiant ORCID ou que vous n'en ayez jamais créé, vous repartirez en sachant comment faire compter vos données océaniques dans votre dossier scientifique. Apportez vos questions pour la période de questions en direct.

This case study is about building CIOOS Metadata Reviewer, a hybrid AI-assisted quality-assurance system that pairs deterministic rule checks with language-model judgment. Lessons learned and future developments are also discussed.

Wanted to share a valuable resource I came across for anyone working at the intersection of data science, ecology, and oceanography: the SECOORA AI Gateway (https://ai-gateway.secoora.org/).

Processing thousands of hours of underwater audio or large volumes of survey footage can be a massive bottleneck for research labs. The Southeast Coastal Ocean Observing Regional Association (SECOORA) developed this hub to make AI adoption much simpler:

1. Interactive Workflow Selector: A guided tree that helps you figure out which ML/computer vision/bioacoustic approach suits your dataset.

2. Reproducible Notebooks: Practical, cloud-ready templates for real tasks (e.g., vessel noise detection, species identification, visual tracking).

3. Community-Driven: Curated references and benchmarks specifically geared toward marine research rather than generic datasets.

Definitely worth bookmarking if you or your team work with environmental sensor data!

This is an exciting opportunity to work with ocean datasets, imaging, sensors and emerging technologies, while applying AI/ML and computer vision to real-world marine challenges.

This position will play a significant role with the Canadian Integrated Ocean Observing System (CIOOS), helping transform ocean observations into accessible, discoverable and usable data and information that can support research, innovation, decision-making and ocean stewardship across Canada.

If you’re ready to put your technical skills to work advancing ocean data and innovation, we’d love to hear from you!

It’s a Checklist to Examine AI-readiness for Open Environmental Datasets, authored by the ESIP Data Readiness Cluster. It’s designed to help data users, producers, and managers assess how ready a dataset is for AI applications and where it needs improvement.

Since we all spend so much time cleaning and prepping ocean data for machine learning models, this seems like a really solid framework to evaluate whether a dataset is usable before we dive into it. It was built using a matrix from the OSTP Subcommittee on Open Science, with input from folks at NOAA, NASA, and USGS.

Link: https://esip.figshare.com/articles/online_resource/Checklist_to_Examine_AI-readiness_for_Open_Environmental_Datasets/19983722?file=35578457

What We Covered

We kicked off the meetup with some short, friendly presentations to set the stage:

• Exploring CIOOS: We took a look at the public ocean datasets available through the Canadian Integrated Ocean Observing System (CIOOS) catalogue.

  • Data Catalogue: https://catalogue.cioos.ca/

  • Data Explorer: https://explore.cioos.ca/?lang=en

  • Catalogue Map: https://cataloguemap.cioos.ca/

• AI Agent Prompt Design: We discussed basic prompting techniques—how to talk to an AI agent in plain language to get reliable code and avoid common pitfalls.

• ML & Deep Learning 101: We shared a jargon-free overview of how AI learns from data and why it has become such a useful tool for ocean science.

  • Check slides here to see the AI agent prompt design and ML & DL 101:
    AI-Workshop-Building-Bridges

  • Check the Vibe-Coding-Kit developed for the participants here: Event GitHub Repo

What Was Built

Participants followed Kedar’s live demonstration including getting access to the AI coding agent, choosing a dataset from the CIOOS catalogue and beginning guiding the agent to build and train the ML model. Some of the practical pipelines and tools built during the session included:

• Automated Data Fetchers: Systems designed to automatically download, clean, and organize raw ocean data.

• Predictive ML Models: Basic machine learning models set up to find patterns and learn from the selected datasets.

Here is the chat log with the prompts and responses from the session. Here is the chat log of an example of an ideal chat for this session. The final deliverable from the example chat is loaded into this GitHub repository. 

If you’d like to try the AI Coding Agent or revisit what we covered in the session, please review the log and fill out the form to receive an API key (we cover the token cost). You may also want to review the AI Coding Agent’s GitHub page for setup instructions.

We’re planning a follow‑up session so more participants can try the AI Coding Agent themselves. If you weren’t able to attend on August 13 and would like to join the next session, please add your name to the waitlist.

🏥 The AI Clinic is Now Open!

The live session may be over, but the learning and troubleshooting continue in our AI Clinic!

If you’re continuing your project, tackling a new dataset, or encountering issues with your AI Coding Agent, feel free to stop by the AI Clinic page and share your questions.

Here are some ways you might use the Clinic thread (not an exhaustive list):

• Share your progress: Post screenshots of the charts or models you built.

• Get troubleshooting help: If your AI agent is giving you errors or you are stuck on a specific prompt, paste the details below.

• Ask our experts: Kedar, Hao, and the community will be checking in on this thread periodically to help you unstick your code and chat about ocean data.

If you missed our live session, or simply want to revisit the insights shared, you can now watch the full recording.

youtube.com/watch?v=6robnyc7FZ8&feature=youtu.be

About this Session

Navigating professional data analysis software often involves complex interfaces and endless button configurations. This learning session explores a paradigm shift in data visualization by showcasing the integration of Large Language Models into geophysical data analysis. Led by Dr. Matthew Widlansky from the University of Hawaii Sea Level Center, this event will introduce the Intelligent Data Exploring Assistant (IDEA), a novel tool designed to help users efficiently explore and visualize datasets, specializing in geophysical data like sea levels.