The Faculty of Forestry and Environmental Management (ForEM) at the University of New Brunswick (UNB), Fredericton campus invites applications for a full‑time, 5‑year term Assistant Teaching Professor position in Digital Forestry, with an anticipated start date of 1 September 2026 (or as negotiated), subject to final budgetary approval.

The University of New Brunswick respectfully acknowledges that its Fredericton campus sits on unsurrendered and unceded traditional Wolastoqey land. The lands of Wabanaki people were recognized in a series of Peace and Friendship Treaties to establish an ongoing relationship of peace, friendship and mutual respect between equal nations. The river that runs by our university is known as Wolastoq, along which live Wolastoqiyik, “the people of the beautiful and bountiful river.” Wolastoq is also known as the Saint John River.

This is a teaching‑stream academic appointment with a primary focus on graduate education and curriculum development within the professional (non‑thesis) Master of Forestry (MF) degree program. The successful candidate will lead the development and delivery of a new Digital Forestry stream (i.e., a set of coordinated courses and applied experiential learning components) within the MF program.

The position is situated at the intersection of forestry and data science and is designed to support the evolution of the MF program to better reflect emerging digital, analytical, and technology‑enabled approaches to forest management.

About the Digital Forestry Stream

ForEM is developing a new Digital Forestry stream within the Master of Forestry (MF) professional degree program, intended to prepare graduates for data‑intensive, technology‑enabled careers in forest management, policy, planning, and decision support.

The Digital Forestry stream will:

• Be embedded within the existing professional MF program
• Offer a cohesive set of graduate‑level courses and applied learning experiences
• Bring together students with backgrounds in forestry, computer science, and geomatics
• Emphasize interdisciplinary, team‑based learning grounded in real‑world forest management challenges

A distinguishing feature of the stream will be a practice‑oriented, integrated management practicum, where students apply advanced data analytics, geospatial tools, and digital technologies to contemporary forestry problems in collaboration with external partners.

While initially focused on the MF program, the Digital Forestry stream is expected to inform and support related undergraduate and professional learning opportunities over time, allowing digital forestry concepts and tools to be incorporated into senior undergraduate courses and experiential offerings as appropriate.

Key Responsibilities

The Assistant Teaching Professor in Digital Forestry will:

• Co-lead the design, development, and coordination of the Digital Forestry stream within the Master of Forestry program
• Develop and teach graduate‑level courses aligned with digital forestry 
• Design and oversee integrated, interdisciplinary management practicums within the MF program
• Mentor and supervise MF-DF students from diverse academic backgrounds
• Collaborate with faculty across ForEM and partner units (e.g., Computer Science, Geomatics)
• Engage with government, industry, Indigenous organizations, and other external partners to support applied learning
• Contribute to service activities within ForEM and the University
• Maintain excellence in teaching and pedagogical innovation consistent with a teaching‑stream academic appointment

Selective involvement in senior undergraduate teaching or curriculum development may occur as the stream and related offerings mature.

Potential Teaching Areas 

Teaching responsibilities will evolve with the development of the Digital Forestry stream and may include graduate‑level courses or modules in areas such as:

• Digital and Precision Forestry
• Advanced Forest Data Analytics and Visualization
• Remote Sensing and LiDAR Applications in Forestry
• Geospatial Analysis for Forestry and Environmental Management
• Big Data Management in Natural Resource Systems
• Data-driven Forest Operations Optimization
• Machine Learning and AI Applications in Forestry
• Automation, Autonomous Technologies, and AI-Enabled Robotics
• Decision Support Systems for Sustainable Forest Management
• Integrated Digital Forestry Practicum (professional, applied, interdisciplinary)

Qualifications

Applicants must have:

• A master’s degree in Forestry, Environmental Science, Geomatics, Computer Science, Data Science, or a closely related field (a PhD is considered an asset)
• Demonstrated expertise relevant to digital forestry, forest informatics, geospatial analysis, or data‑driven natural resource management
• Evidence of or strong potential for excellence in graduate‑level teaching, particularly within professional degree programs
• Interest in interdisciplinary, applied, and experiential education
• Ability to collaborate effectively across disciplines and with external partners

Experience in professional forestry practice, government or industry settings, or applied program development is considered an asset.

Application Process

Applicants should submit:

1. A cover letter outlining interest and relevant experience
2. A curriculum vitae
3. A statement of teaching philosophy, with emphasis on graduate and/or professional education
4. A brief statement outlining a vision for the Digital Forestry stream within the MF program
5. Names and contact information for three referees

Applicants can apply by clicking here: https://jobs.careerbeacon.com/apply/2234158?utm_source=sharepage-jobboards&utm_campaign=refer&utm_medium=in-app. 
Review of applications will begin August 4, 2026, and will continue until the position is filled.

The salary for the position depends on the rank at which the successful candidate is hired. Faculty salary grids by rank are available here: https://www.unb.ca/hr/_assets/documents/salary-grids.pdf . Salary and fringe benefits are governed by Sections 35 and 36B of the Association of University of New Brunswick Teachers (AUNBT) 2025-2029 Collective Agreement.

Short-listed candidates will be required to provide satisfactory proof of credentials including appropriately certified translations of credentials into English, as applicable.

The University of New Brunswick is committed to employment equity and fostering diversity within our community and developing an inclusive workplace that reflects the richness of the broader community that we serve. The University welcomes and encourages applications from all qualified individuals who will help us achieve our goals, including women, visible minorities, Aboriginal persons, persons with disabilities, persons of any sexual orientation, gender identity or gender expression. Preference will be given to Canadian citizens and permanent residents of Canada.