Pica Code: IR-2026-010. Artificial intelligence methods for multimodal data integration in High-Grade Serous Ovarian Cancer

Scientific-Disciplinary Group

09/IINF-05 - Information Processing Systems

Description

The activity covered by the assignment consists of the development of artificial intelligence methodologies for the integrated analysis of digital histopathology, genomic and clinical data, aimed at predicting response to chemotherapy treatments in ovarian cancer (HGSOC).The Objectives of the assignment include the design and implementation of models based on Transformer and statespace architectures (Mamba) for representation learning from Whole Slide Images and molecular data, as well as the development of data integration strategies addressing missing modalities (partial absence of one or more data sources) for the modelling of clinically relevant response indicators, such as sensitivity to platinum-based chemotherapy and pathological treatment response scores. (omissis)

Compensation

33,708 Euro

Job posting website

https://titulus-unimore.cineca.it/albo/

Number of positions

1

Maximum duration

36.0

Funding body

UNIMORE

How to apply

Other

Selection process