Postdoctoral Researcher in Computer Science

Postdoctoral Researcher in Computer Science

Örebro University

Örebro, Sweden

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.

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.

Assessment criteria

A basis for the assessment is the applicant’s ability to disseminate information and communicate; collaborate and engage with the wider community; and facilitate utilisation of the university’s research. In addition, the applicant’s suitability for the position will be assessed. Suitability refers to the applicant demonstrating the personal qualities required to successfully perform the duties and responsibilities at hand, the ability to cooperate with other members of staff, and the ability to contribute to the development of the operations.

Particular attention is to be paid to the applicant’s prospects of contributing to the future development of both research and education. Importance is also attached to a demonstrated ability and ambition to embark on a career within academia.

• Required: Doctoral degree in a quantitative discipline - statistics, applied mathematics, machine learning, signal processing, robotics, or a closely related field.
• Required: Demonstrated experience in statistical modelling and/or machine learning for regression or distribution estimation, and in time-series or signal processing; proficiency in Python.
• Advantage: Hands-on field or experimental experience acquiring and analysing real-world sensor data (e.g. IMU/accelerometer, vibration), and working with mobile/heavy equipment or in industrial settings; experience with edge/embedded deployment; ROS2.
• Desirable: Domain familiarity with mining, fragmentation, geomechanics, or comminution; a valid driving licence and willingness to conduct site visits in harsh underground conditions.
• Language: Working proficiency in English required. It is not necessary to be familiar with the Swedish language.