HEIBRiDS (Helmholtz International Berlin Research School in Data Science) is an interdisciplinary doctoral program and trains young scientists in Data Science applications within a broad range of natural science domains, spanning from Earth & Environment, to Geosciences, Materials & Energy and Molecular Medicine. The mission of HEIBRiDS is to educate new generations of researchers, who, as skilled data scientists, understand the demands and the challenges of the disciplines in which data science has become indispensable. HEIBRiDS is established jointly between the Helmholtz Association and BIFOLD (Berlin Institute for the Foundations of Learning and Data).
PhD Project at GFZ: Predicting geomagnetic conditions on the Earth from multi-spectral images of the Sun by combining data science and physical models
In this project, we propose to leverage the growing number of highly detailed multi-spectral images of the Sun to improve the prediction of the solar wind streams arriving at the Earth. We propose to exploit the capabilities of modern computer vision and machine learning techniques to register solar images, analyze them and assimilate them in an empirical (data-driven) model. We plan to develop and train a regression model that predicts solar wind based on the large amount of available data (solar wind measurements near the Earth and multi-spectral solar images): the amount of data transmitted by the solar dynamics observatory (SDO) alone is approximately 1TB per day. Huge amounts of historical observations are now available from NASA and associated centers, whereas a large database of solar images from various missions is maintained by GFZ-Potsdam.
PhD Student: Daniel Collin
Supervisors: Prof. Dr. Yuri Shprits, Prof. Dr. Guillermo Gallego (TU Berlin)
Project Duration: 10/2022 – 09/2026
Funding: Helmholtz Association
Website: https://www.heibrids.berlin