Unal Artan

Postdoctoral Researcher in Computer Science at Örebro University , Sweden. This fixed-term, full-time two-year postdoctoral appointment is located at the School of Science and Technology and is centred on machine learning and signal processing for proprioceptive sensing . The project focuses on an industrially relevant sensing challenge: using vibration signals from mining machines to estimate rock fragmentation underground, where conventional cameras and sensors are limited. The research aims to move beyond average fragment-size estimation and recover richer fragment-size distributions, with potential impact on efficiency and energy use across the mining production chain. The post is connected to the Robot Navigation and Perception Lab , the Centre for Applied Autonomous Sensor Systems (AASS) , and Örebro University’s AI, Robotics, and Cybersecurity center (ARC) . The project is carried out in collaboration with Epiroc and Boliden and is funded by the Swedish Energy Agency through Impact Innovation, Swedish Metals & Minerals . The work is highly applied and data-driven, with access to real machines, underground environments, and industrial data. Applicants should hold a doctoral degree in a quantitative discipline such as statistics, applied mathematics, machine learning, signal processing, robotics, or a closely related field. Strong experience in statistical modelling and/or machine learning for regression or distribution estimation, together with time-series or signal processing, is required. Python proficiency is required. English working proficiency is necessary; Swedish is not required. Experience with real-world sensor data, industrial or field work, edge/embedded deployment, and ROS2 is advantageous. Familiarity with mining, fragmentation, geomechanics, or comminution is desirable. The role is intended to support the development of an independent research profile, with opportunities to publish in peer-reviewed venues, present at scientific and industry conferences, and contribute to a strong international research environment. The application deadline is 2026-09-21 .