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We are looking for a postdoctoral researcher in Computer Science for a fixed-term 2-year position at the School of Science and Technology. Subject area The subject area for this position is Computer Science, with a focus on machine learning and signal processing applied to proprioceptive sensing. Background We are looking for a postdoctoral researcher to tackle a hard and impactful sensing problem: developing machine learning approaches for turning the vibration signals of mining machines into precise, bucket-by-bucket estimates of how finely rock has been fragmented underground, where cameras and conventional sensors struggle. Crushing and grinding of ore in the mining sector accounts for roughly 3% of the global total electricity use. Better fragmentation data enables energy and efficiency gains across the entire production chain. The position is funded by an industrial research project in collaboration with Epiroc and Boliden, funded by the Swedish Energy Agency (Impact Innovation, Swedish Metals & Minerals). The two main goals of the project are to advance proof-of-concept results for proprioceptive sensing toward a validated technology and to extend the capabilities of today's state-of-the-art methods to extracting a richer set of material characteristics from piled materials. The position is associated with the Robot Navigation and Perception Lab which belongs to the Centre for Applied Autonomous Sensor Systems (AASS) research environment and Örebro University’s AI, Robotics, and Cybersecurity center (ARC). We are an international team working with robotics and AI applied to real field conditions, and you will have access to real machines, real underground environments, and industrially relevant data, with a clear path from research to deployment. Duties and responsibilities The appointment as a postdoctoral researcher is intended to enable persons who have recently been awarded their doctoral degree to consolidate and develop primarily their research skills. The position offers the opportunity to develop an independent research profile in machine learning and signal processing for proprioceptive sensing, within an active project on rock fragmentation estimation in mining. Building on proven results that estimate the average fragment size from machine vibration signals, the central research challenge is to recover the full distribution of fragment sizes — a substantially richer characterisation that would extend what proprioceptive sensing can deliver. The postdoctoral researcher will help shape how this problem is approached and develop and evaluate methods to address it. There is further scope to investigate how fragmentation relates to material-handling efficiency, and how reliable estimation can run onboard equipment in operational settings, working with real data gathered together with industrial partners. The researcher will publish in peer-reviewed venues, present at scientific and industry conferences, and contribute to the wider research environment at AASS. Qualifications Those qualified for appointment as a postdoctoral researcher are applicants who at the time of appointment hold a doctoral degree or have a degree from abroad deemed to correspond to a doctoral degree. Applicants with doctoral degrees that have been awarded no more than 3 years prior to the application deadline are to be considered first. The applicant may not previously have held a position as a postdoctoral researcher for more than one year in the same subject and at the same higher education institution. The position is for a term of at least 2 years initially but may be extended for a further 1 year. If the person during the period of employment has been on parental leave, the period of employment is to be extended by the corresponding number of days. The period of employment may also be extended in the event of absence due to illness. Assessment criteria To see the job advertisement and the assessment criteria in its entirety, visit