Doctoral Candidate
Pubblicato il 17-08-2026 - Universita Degli Studi Di Firenze in Italia
Organisation/Company Università degli Studi di Firenze Department Scienze della Salute Research Field Biological sciences » Biology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 31 Aug 2026 - 13:00 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within a Research Infrastructure? No
Offer Description
Background:
SPACE-MEL is an EU-funded MSCA Doctoral Network advancing the next generation of spatial single-cell omics technologies for precision medicine. The programme brings together leading European universities, technology providers, clinical partners and innovative companies to address key experimental and computational challenges currently limiting the clinical translation of spatial biology. By integrating multi-omics approaches, enabling the transition from 2D to 3D tissue analysis and developing advanced data interpretation methods,
SPACE-MEL aims to unlock deeper insights into cellular organisation and disease mechanisms. The network will train 15 Doctoral Candidates through an interdisciplinary programme spanning spatial imaging technologies, molecular biology, computational biology, pathology and biomarker discovery.DC13 focuses on Mucosal Melanomas (MuM). Building on its vast experience, UNIFI will carry out a comprehensive Tumor Microenvironment (TME) visualization through double and triple staining followed by computational analyses to detect potential biomarker colocalization. It will correlate the findings with prognostic parameters, refining the prognostic value of the Immunoscore for MuM in order to identify predictive biomarkers and refine TME-based therapies.
Project aim:
The aim of the project is to investigate microenvironmental and sub-clonal heterogeneity in mucosal melanoma during progression. The project will apply spatial multi-omics methods and