Postdoctoral Researcher in Multimodal AI for Cancer Research

29 ago - Rozzano
Humanitas University

? Work location: Via Rita Levi Montalcini 4, 20072 | Pieve Emanuele (MI)
? Contract type: Coordinated and Continuous Collaboration Agreement (Co.Co.Co.)

Why Humanitas
Choosing Humanitas means joining an environment where quality of care is built every day through clinical expertise, innovation and teamwork, where everyone contributes to the patient care journey.

Who we are
Humanitas University is an international institution dedicated to the Life Sciences, closely integrated with the IRCCS Humanitas Research Hospital and the Humanitas hospital network. The University combines education, research, and clinical practice within a highly international environment. Medicine and Surgery and MEDTEC School are taught entirely in English, and the University currently hosts more than 3,000 students, with international students accounting for 43% of the Medicine cohort. Teaching activities take place on a modern, sustainable 35,000 sqm Campus designed to foster interaction among students, researchers, and faculty,



with facilities including the Anatomy Lab and the Simulation Center – the only center in Italy fully accredited by the European Society for Simulation in Medicine for excellence in healthcare simulation training.

The context
The Computational Biology Laboratory led by Prof. Charlotte Ng is seeking a highly motivated data scientist or AI researcher to develop computational methods for precision oncology. Our research combines clinical data with bulk, single-cell and spatial omics, digital pathology and other biomedical data to study tumour heterogeneity and improve patient stratification and treatment response prediction.
The successful candidate will develop and evaluate machine learning approaches for modelling complex, heterogeneous and incompletely observed biomedical data. The work may encompass multimodal representation learning, deep generative modelling, transfer learning and robust predictive modelling. The candidate will work closely with computational bi

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