Master-Level Internship (Spring 2026, with potential progression to a PhD)

This project will re-examine the link between high-energy IceCube track events and Fermi-LAT blazars by integrating the forthcoming IceCat-II catalogue, which will consist of 365 well-reconstructed alerts spanning May 2011 – 2 January 2025. Using IceCat-II together with the latest Fermi-LAT AGN catalogue, the student will rebuild the analysis pipeline, deploy state-of-the-art machine-learning algorithms, and test whether the results reported in Enzo Oukacha’s PhD thesis persist or disappear in the enlarged sample. If IceCat-II is still unavailable by spring 2026, the project will pivot to a refined study based on the existing IceCat-I dataset.

This internship is ideal for a student eager to work daily with Python-based machine-learning tools, handling everything from data ingestion and feature engineering to model training, evaluation, and statistical validation, to uncover subtle signals in complex astroparticle-physics data.

Because catalogue release schedules and analysis directions can evolve quickly, a proactive, positive, and flexible attitude will be essential for success.

For further information, feel free to contact me via email.