PhD and MSc thesis topics

1. Developing an empirical bow shock model using deep learning codes
   

   When I worked at the Finnish Meteorological Institute from 2010 to 2011 I developed an algorithm to determine the bow shock time and location from Cluster measurements. The task is to test the prediction abilities of the code and improve its capability using deep learning methods. The tested and improved code is applied for the measurements of the Cluster, Time History of Events, and Macroscale Interactions during Substorms (THEMIS) and other spacecraft to determine the time and location of the bow shock transitions. The candidate will create a new empirical bow shock model depending on the data of Advanced Composition Explorer (ACE) and Deep Space Climate Observatory (DSCOVR) solar wind monitoring spacecraft; furthermore the Kp and Dst geomagnetic indexes.

Last modified by Gabor FACSKO on May 12, 2026