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Left: The atomic hydrogen gas (or HI gas) in the Milky Way foreground toward the Magellanic Clouds. Right: The Galactic magnetic field revealed by Planck using polarized emission from dust at submm wavelengths.

The Milky Way's magnetic field is critical for shaping the structure and evolution of the galaxy, regulating star formation, and transporting cosmic rays. Understanding the interaction between the magnetic field and atomic HI gas is key to unraveling the galaxy's dynamics and evolution.

Previous studies have shown that the magnetic field and interstellar dust appear to align well in the Milky Way foreground toward the Magellanic Clouds. This study will probe the correlation of magnetic field and the atomic HI gas in the region. We will leverage the unprecedented resolution of the Galactic ASKAP survey, which has observed the HI gas with a resolution of 30 arcseconds. We will distinguish the cold and warm phases of HI gas using advanced methods such as decomposition and machine learning. We will then determine the orientation of gas flows in both phases using computer vision algorithms. A comparison with the magnetic field revealed by the Planck Collaboration will shed light on the relationship between HI gas and the Galactic magnetic field.

This project requires only programing skills. Prior knowledge and experience in Machine Learning, Deep Learning, and Gaussian fitting techniques would be beneficial. However, even if you are not familiar with these techniques, the project offers an excellent opportunity to learn and apply these advanced methods in a real astrophysical context.