Viviana Gammaldi

The Universidad San Pablo CEU in Madrid, Spain, invites expressions of interest for a PhD position in the Doctorate Program in Engineering and Technological Development in Industrial, Biomedical and Computational Applications. The selected candidate will join the AstroLearning (Astrophysics and Machine Learning) research group, focusing on cutting-edge topics in modern astrophysics, cosmology, and the application of machine learning tools to areas such as dark matter, indirect searches, gamma-ray telescopes, CTAO, black holes, gravitational waves, and stellar physics. The research group, led by Associate Professor Viviana Gammaldi, collaborates internationally and is part of the Cherenkov Telescope Array Observatory (CTAO) and the Spanish Virtual Observatory. The group is committed to both advanced research and science outreach, including the use of artificial intelligence for educational content creation. The PhD thesis may be co-supervised with Spanish or international institutions, providing a global research environment. Applicants must hold both a Bachelor’s and Master’s degree in Physics, Astrophysics, Engineering, Mathematics, or Computing Science, with a total of at least 300 ECTS credits. An excellent academic transcript is essential, with a preferred average grade above 8.0 on the Spanish scale. Language certification in English or Spanish at minimum B2 level is positively evaluated. The position is intended for highly motivated and excellent candidates who wish to jointly apply for PhD fellowships through national, regional, or local calls. Funding is not guaranteed and depends on the outcome of these applications. To apply, send your CV, complete academic transcripts, and a brief motivation letter to Dr. Viviana Gammaldi ([email protected]) and/or Dr. Belén López Martí ([email protected]) by February 1, 2026. For more information about the program and research group, visit the provided links. This opportunity is ideal for candidates interested in astrophysics, cosmology, machine learning, and computational applications in physics and engineering.