PhD Position in AI for Forest Robotics
Develop real-time machine learning models to enable 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 interdisciplinary applications in forestry and sustainability.
Overview
This PhD position at the Norwegian Institute of Bioeconomy Research (NIBIO) focuses on advancing AI-driven forest robotics. The candidate will design incremental machine learning architectures to interpret 3D point cloud data and camera imagery in real time, enabling robots to navigate and localize within forest environments. The work bridges computer vision, robotics, and forestry, addressing challenges in real-time scene understanding and sensor data processing. The successful applicant will collaborate with NIBIO’s field robots and contribute to sustainable forestry solutions. The position is based in Ås, Norway, and involves fieldwork in Norwegian forests.
What you'll do
- Design and implement machine learning architectures capable of incrementally interpreting 3D point cloud data and camera imagery for real-time forest scene understanding.
- Develop compact representations of forest structures to support localization, place recognition, and traversability in real-time environments.
- Adapt deep learning models to handle live sensor data challenges, including sparsity, uneven sampling, motion distortion, and partial observations.
- Implement and evaluate proposed systems on embedded hardware and NIBIO’s robot platforms, ensuring practical applicability.
- Conduct field experiments in Norwegian forests to validate the performance and robustness of the developed systems.
- Collaborate with interdisciplinary teams to integrate findings into sustainable forestry solutions.
Requirements
Degree required: Master's degree or equivalent five-year degree in data science, machine learning, robotics, or a related field. Must be completed before the start date.
Degree offered: PhD
Language: English; strong command of oral and written English required. Norwegian language training (up to A2 level) provided if needed.
Instruction: English
- Experience implementing and modifying deep learning architectures, particularly for 3D data (e.g., point clouds).
- Proficiency in Python and modern deep learning frameworks such as 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).
- Experience with robotics and state estimation (e.g., SLAM, sensor fusion, ROS/ROS2).
- 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 previous research fellowship funded by the Norwegian Research Council.
- Must meet NMBU’s admission requirements for the PhD programme.
Funding & terms
How to apply
Deadline: 2026-10-18
Applicants must submit their CV electronically via the provided application link. If invited for an interview, originals of diplomas and letters of recommendation must be presented, along with copies attached to the electronic application. Background checks are conducted on final candidates.
- CV
- Cover letter
- Diplomas and transcripts (BSc and MSc)
- Letters of recommendation (3 minimum)
- Proof of English proficiency (if applicable)
Contact
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