About the position
## About the position The position is a three year position, based at Ås, 30 km south of Oslo. The candidate will be enrolled at NMBU and works with the department's field robots. To be a current applicant, you cannot have previously held a research fellowship position at NIBIO, and you cannot have a previous doctorate or have previously held a research fellowship position with funding from the Norwegian Research Council. If you do not have skills in Norwegian, Swedish or Danish at level A2 upon employment, NIBIO will offer free Norwegian language training with the goal of achieving Norwegian skills at at least this level. ## Main responsibilities - Develop machine learning architectures that interpret 3D point cloud data incrementally, for real-time use, building an understanding of the surrounding forest as new observations arrive. - Investigate compact representations of forest structure, and how they support localisation, place recognition and scene understanding - Adapt models to the properties of live sensor data: sparse, unevenly sampled, motion-distorted and partially observed - Implement and evaluate the resulting systems on embedded hardware and on NIBIO's robot platforms ## Will be evaluated positively - Deep learning on 3D and sensor data: point clouds, voxel or sparse representations, transformers, segmentation, registration. Experience designing or adapting architectures rather than only applying existing ones. - Real-time and resource-constrained inference: quantisation, pruning, distillation, CUDA, embedded accelerators. C++ or other systems programming. - Robotics and state estimation: SLAM, sensor fusion, place recognition, ROS/ROS2. Experience with UAVs, ground robots, or agricultural and forestry machinery. - Practical experience building or integrating physical sensing systems and running field experiments - Knowledge of forestry, remote sensing or ecology - Knowledge of Norwegian or another Scandinavian language ## Personal qualifications - Ability to work independently on open-ended research problems, from idea through implementation to field validation - Strong analytical ability and capacity to learn unfamiliar methods and tools quickly - Commitment and enthusiasm for working as part of an ambitious research team - Good communication and interpersonal skills, and the ability to collaborate with colleagues and external partners from different academic backgrounds ## How to apply for the position Please send your application with CV electronically via the link on this page. Take originals of diplomas and letters of recommendation with you if invited to an interview, and submit a copy of them as an attachment along with the electronic application/CV. We conduct background checks on final candidates as part of our recruitment process.
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