Publisher
source

Rasmus Astrup

4 months ago

PhD Scholarship: Deep Learning Methods for Characterizing Forest Structure with 3D Point Clouds Norwegian University of Life Sciences in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Norway

University

Norwegian University of Life Sciences

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Where to contact

Official Email

Keywords

Computer Science
Data Science
Environmental Science
Deep Learning
Biology
Remote Sensing
Biodiversity
Photogrammetry
Lidar Technology
Computer Vision
Rainforest Ecology
Self-supervised Learning
Landscape
Point Cloud
Machine learning

About this position

The Norwegian University of Life Sciences (NMBU) is offering a 3-year PhD position within the Faculty of Environmental Sciences and Natural Resources Management (MINA), focused on developing deep learning models for 3D forest point clouds. This position is part of the SmartForest research-driven innovation center, which aims to advance digitalized and sustainable forest management using cutting-edge technologies. The successful candidate will work on developing both supervised and self-supervised deep learning algorithms to process and analyze 3D point cloud data from LiDAR and photogrammetry, with the goal of characterizing forest ecosystem structure and function. The project seeks to push the boundaries of current computer vision models, expanding their applicability from high-resolution, small-area datasets to lower-resolution, landscape-level datasets. The candidate will be expected to contribute to a variety of downstream tasks, including the assessment of forest structure and biodiversity. Applicants must have a master's degree in machine learning, computer science, or a forest-related field with a focus on remote sensing, and demonstrate experience with deep learning. Additional skills in handling forest ecosystem data, 3D point clouds, programming (including Docker and containerization), and proficiency in Norwegian or another Scandinavian language are valued. The position offers a starting salary of NOK 550,800 per year and follows national guidelines for PhD scholars in Norway. The application process requires submission of a motivation letter, CV, certified academic documents, proof of English proficiency, references, and other relevant documentation. The faculty is known for its vibrant research culture and international quality, with expertise spanning geology, hydrology, soil science, environmental chemistry, forestry, ecology, and more. NMBU provides a supportive and interdisciplinary environment, with a strong focus on innovation and collaboration. The application deadline is November 10, 2025. For further information, applicants may contact Professors Rasmus Astrup or Terje Gobakken.

Funding details

Available

What's required

Applicants must have a master's degree in machine learning, computer science, or a forest-related field with a focus on remote sensing, and experience with deep learning. A strong academic background corresponding to a five-year Norwegian degree programme with 120 ECTS credits at master's level is required, including a master's thesis or individual written assignment of at least 20 ECTS credits. An average grade of B or above in the ECTS grading system and proficiency in both written and oral English are mandatory. Experience working with data from forest ecosystems, 3D point clouds, strong programming skills, and experience with Docker and containerization are emphasized. Proficiency in Norwegian or another Scandinavian language is desirable. Applicants must have good interpersonal and communication skills, strong analytical and problem-solving abilities, and the ability to work under pressure and collaborate with industrial partners and diverse research teams.

How to apply

Apply online via the University's Web Recruitment System by clicking the 'Apply for this job' button. Register an account and complete the online application form. Attach a motivation letter, complete CV, certified copies of academic diplomas and certificates, documentation of English proficiency, names and contact details for two references, and any additional relevant documentation. Ensure your CV is entered in JobbNorge's CV form.

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