Ilaria Gandin

PhD opportunity in Applied Data Science and Artificial Intelligence at the University of Trieste , in collaboration with the Cardiothoracovascular Department of Azienda Sanitaria Universitaria Giuliano Isontina (ASUGI), Trieste . The project title is “Deep learning methods for the derivation of cardiac phenotypes from ECG and imaging, for genetic characterization and early diagnosis in cardiomyopathies” . The research sits at the intersection of computer science , medical science , biostatistics , biomedical engineering , biology , and statistics . Key topics include self-supervised representation learning from high-dimensional biomedical signals, latent-space modelling, multi-modal data integration, rare variant association analyses, and polygenic modelling to study the genetic architecture and biological basis of cardiovascular phenotypes. The project is embedded in an international academic network with collaboration opportunities across research groups in statistical methods for health data, genomics, and AI. This is a fully funded 3-year PhD position . A visiting research period abroad is also supported during the doctorate. Eligibility is competitive and includes assessment of qualifications and an oral interview. The call indicates that applicants should hold an Italian master's degree or a suitable foreign academic qualification. English proficiency will be assessed during selection. Deadline: 25 May 2026. The official application window runs from 22/04/2026 to 25/05/2026. For further information, contact Ilaria Gandin at [email protected] . Apply via the University of Trieste PhD application portal and read the official call and attachment before submitting.