MSc student - Forest Research Assistant - Research Affiliate Program

• Department: Natural Resources Canada - Canadian Forest Service - Atlantic Forestry Centre
• Reference number: RSN26J-084202-000430
• Selection process number: 2026-RSN-EA-CFS-682177
• Location: Fredericton (New Brunswick)
• Salary: Scholarship of approximately $25,500/year divided into 3 equal installments each year.
• Who can apply: Persons residing in Canada, and Canadian citizens and Permanent residents abroad.
• Closing date: 30 November 2026

About the position DutiesWe are seeking an MSc student interested in remote sensing, tree physiology, and genetics to identify productive and resilient black spruce seedlings under climate change-related stressors. Climate change is increasing the frequency and severity of drought events while also influencing forest insect disturbances such as spruce budworm outbreaks, both of which threaten forest health and productivity.
This project will investigate the combined effects of drought stress and spruce budworm defoliation on a black spruce breeding population grown in a greenhouse. The student will assess a broad range of physiological and morphological traits and use multi-spectral remote sensing technologies to develop high-throughput phenotyping approaches. These phenotypic data will then be integrated with genotyping information to identify seedlings and families with enhanced resilience to multiple stressors. The experiment has already been established in the AFC greenhouse. The student will be responsible for plant maintenance, data collection, processing, and analysis throughout the project. Work environmentAt Natural Resources Canada, a federal government job means developing leadership skills, fostering teamwork, and supporting creativity and innovation. We know it takes people from diverse pools of talent to make this happen. That is why we are looking for people like you. As an employee at Natural Resources Canada you can enjoy diverse employment opportunities, a range of career development programs, and a learning culture that supports you to learn on an ongoing basis. We support balancing your work and private life by offering the benefits of flexible work arrangements. Intent of the process The intention is to staff one student position for the completion of a masters degree supervised by Dr. Funda Ogut (Canadian Forest Service - Atlantic Forestry Centre). Positions to be filled 1 Important messages You must provide proof of your education credentials, and a list of courses may be required.
Persons are entitled to participate in the appointment process in the official language of their choice.
A random and/or top-down selection of candidates may be used in the determination of those to be given further consideration in the assessment process.
Candidates from outside the public service may be required to pay for travel and relocation costs associated with this selection process.
Successful completion of both a RAP work assignment and your educational program may lead to a temporary or permanent federal public service position for which you meet the merit criteria and conditions of employment.
For further information on the Research Affiliate Program (RAP), please visit: https://www.canada.ca/en/public-service-commission/jobs/services/recruitment/students/research-affiliate-program.html
Natural Resources Canada is committed to employment equity and building strength through diversity. We welcome applications from qualified people and encourage members of the designated groups (Aboriginal Peoples, Persons with Disabilities, Visible Minorities and Women) to apply and to self-identify.
For this selection process, it is our intention to communicate with candidates via email for screening and assessment purposes (including issuing screening results and sending invitations for written tests and interviews). To that end, you must include a valid email address in your application. It is your responsibility to ensure that this address is functional and that it accepts messages from unknown users. It is also your responsibility to ensure accurate information is provided and updated as required.
We thank all applicants for their interest in our position(s). For the purpose of this staffing process, only candidates selected for further assessment will be contacted. Conditions of employment• Reliability Status security clearance - This factor is not used at the screening stage; the hiring department is responsible for the security clearance process.
• Possession of valid Canadian driver’s license.
• Willingness and ability to travel from home base for extended periods.
• Willingness and ability to conduct fieldwork*.
*For fieldwork, the student must obtain certifications as needed, including remote first aid/CPR. You need (essential for the job) Applied / assessed at a later dateEducation:
• Bachelor of Science in forestry, environmental science, biology, remote sensing, or other relevant fields.
• Currently enrolled or eligible to enroll in a MSc program in the Faculty of Forestry and Environmental Management at University of New Brunswick.Experience:
• Experience conducting scientific research related to plant physiology and remote sensing, and their integration in the genomics aspects of this project.
• Experience with basic programming such as R, Fortran or Python languages.
Note: In the context of student recruitment in the Federal Public Service, the experience can be acquired through the studies, work experience, or volunteer activities.Knowledge:
• Knowledge of plant physiology.
• Knowledge of forestry.
• Knowledge of statistics.Abilities:
• Ability to effectively communicate orally.
• Ability to effectively communicate in writing.
• Ability to work independently and collaboratively.
• Ability to work in greenhouse and outdoor environments.Personal Suitability:
• Initiative
• Motivated
• Integrity and respect
• Adaptability Language requirements (essential for the job) Applied / assessed at a later date English essential You may need (asset qualifications) May be applied / assessed at a later date• Knowledge of hyperspectral remote sensing, LiDAR, genetics.