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Cancer research today requires more than biological insight – it demands mathematical innovation, engineering precision, and advanced computational approaches. Soft tissue sarcomas remain among the most difficult tumors to treat due to the complexity of their tumor microenvironment and vascular architecture. We believe that by quantitatively and spatially modeling this complexity, we can unlock new therapeutic strategies and improve patient outcomes. Our mission is to transform cancer care through computational modeling and spatial analysis of tumor vasculature.
Responsabilità
Developing algorithms for image segmentation, feature extraction, and 3D vascular reconstruction
Building predictive models using Gaussian Processes, spatial regression, and Bayesian inference
Designing and deploying computational pipelines for multimodal data integration, including spatial omics and imaging
Collaborating within an interdisciplinary team to translate computational advances into clinically relevant insights
Requisiti
Hold a PhD in Applied Mathematics, Biomedical Engineering, Computer Engineering, Computer Vision, Image Analysis, Bioinformatics, or a related discipline
Have strong programming skills in Python and/or R, with experience in high-performance computing (HPC)
Are familiar with spatial data analysis, statistical modeling, and quantitative approaches
Are motivated, independent, and able to work effectively in a collaborative research environment
Have an interest in cancer biology and a willingness to learn and engage with translational research questions
Preferibile
Experience with computer vision libraries such as OpenCV or scikit-image
Knowledge of vascular network modeling, fractal geometry, or advanced statistical learning
Previous work integrating imaging and omics data
Cosa offriamo
The opportunity to contribute to cutting-edge, high-impact oncology projects
Access to state-of-the-art computational and imaging infrastructure
Collaboration with experts across mathematics, engineering, and cancer biology
Professional growth within an innovative and internationally connected research network
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