6. Impact of small-scale EUV brightenings on the solar atmosphere: insights from high-resolution Solar Orbiter data

ESA supervisor: Henrik Eklund
Collaborator(s): Andy To

Site: ESTEC

This project will investigate small-scale brightenings in the solar atmosphere using high-resolution EUV observations from the Extreme Ultraviolet Imager (EUI) onboard Solar Orbiter. These transient brightenings, often associated with localized magnetic activity, are thought to play a role in coronal heating and mass transfer to the solar wind. Despite their abundance and significance, many aspects of their statistical properties and magnetic environment remain unexplored.

The selected candidate will compile and analyze a diverse set of EUI image sequences and identify brightenings using existing detection techniques or threshold-based methods. Artificial intelligence methods may also be explored to improve or automate the detection process. These detections will be combined with measurements from other instruments onboard Solar Orbiter, such as magnetic field data from the Polarimetric and Helioseismic Imager (PHI), as well as from other observatories,  including the Solar Dynamics Observatory (SDO), the Interface Region Imaging Spectrograph (IRIS), and ground-based observatories. Using this multi-instrument dataset, the selected candidate will investigate how the occurrence and properties of brightenings vary across regions of the solar disk with different magnetic activity and characteristics.

The project will develop skills in solar physics, handling large datasets, feature detection, multi-wavelength analysis, and statistical interpretation. It may also involve the application or evaluation of AI-based tools for pattern recognition or classification. The outcome is expected to provide new insight into the statistical distribution and characteristics of small-scale energy release events in the solar atmosphere, contributing to ongoing efforts to understand the mechanisms that heat the corona and drive the solar wind.

Project duration: 6 months.

Desirable expertise or programming language:

  • Applicants should be comfortable working in Python and have experience analyzing scientific or image-based datasets. Prior exposure to solar physics is helpful but not essential.
  • Strong analytical thinking and a careful approach to data interpretation and methodology are important.
  • An interest in machine learning approaches for feature detection or classification is desirable.

To apply for this project please fill in an online application form through the following link.

To see the full list of Internships available at ESA please go to our website for ESA Career Opportunities.