PhD Position in AI for Forest Robotics
Develop real-time machine learning models for autonomous forest navigation using LiDAR and camera data.
Best for:Best for machine learning researchers with expertise in deep learning, robotics, and real-time systems who are passionate about applying AI to sustainable forestry solutions.
Overview
This PhD position at NIBIO in Norway focuses on advancing AI-driven robotics for forest navigation. The project aims to create real-time, incremental machine learning systems capable of interpreting 3D point cloud data from LiDAR and camera imagery to enable autonomous robots to understand and traverse forest environments. The successful candidate will work on developing novel algorithms for real-time scene understanding, localization, and traversability assessment, with applications in sustainable forestry. The position is based at Ås, near Oslo, and involves collaboration with NMBU’s field robotics team. The candidate will be enrolled in a PhD programme at NMBU and will contribute to cutting-edge research at the intersection of robotics, computer vision, and forestry.
What you'll do
- Develop machine learning architectures to interpret 3D point cloud data incrementally for real-time forest scene understanding.
- Investigate compact representations of forest structure to support localization, place recognition, and scene understanding.
- Adapt deep learning models to handle live sensor data characteristics, such as sparsity, uneven sampling, motion distortion, and partial observations.
- Implement and evaluate proposed systems on embedded hardware and NIBIO’s robot platforms.
- Conduct field experiments to validate the performance of developed algorithms in real forest environments.
- Collaborate with interdisciplinary teams to integrate AI solutions into forestry operations.
Requirements
Degree required: Master's degree or equivalent five-year degree in data science, machine learning, robotics, or a related field, completed before the start date.
Degree offered: PhD
Language: English; strong command of oral and written English required. Norwegian language training (up to level A2) provided if needed.
Instruction: English
- Experience implementing and modifying deep learning architectures, particularly for 3D data.
- Proficiency in Python and modern deep learning frameworks (e.g., PyTorch or TensorFlow).
- Strong programming skills with experience in systems programming (e.g., C++).
- Familiarity with real-time and resource-constrained inference techniques (e.g., quantization, pruning, CUDA).
- Knowledge of robotics and state estimation (e.g., SLAM, sensor fusion, ROS/ROS2).
- Ability to work with UAVs, ground robots, or agricultural/forestry machinery.
- Willingness and physical ability to conduct outdoor fieldwork in Norwegian forests.
- Cannot have previously held a research fellowship position at NIBIO.
- Cannot have a prior doctorate or a research fellowship funded by the Norwegian Research Council.
- Must fulfill NMBU’s requirements for admission to the PhD programme.
Funding & terms
How to apply
Deadline: 2026-10-18 (Europe/Oslo)
Applicants must submit their CV electronically via the provided application link. If shortlisted, original diplomas and letters of recommendation must be presented during the interview and submitted as attachments. Background checks are conducted on final candidates.
- CV
- Cover letter
- Diplomas and transcripts (originals or certified copies)
- Letters of recommendation (3 minimum)
- Proof of English proficiency (if applicable)
Contact
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