Senior Postdoc: AI-Driven Radiomics for Precision Oncology

Vall d'Hebron Institute of Oncology (VHIO); Barcelona; Presencial; EUR 42.000 - 56.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible remuneration program

Spanish/English courses

WellHub sports facilities

Weekly physiotherapy sessions

Career development opportunities

Inclusive workplace

Descripción de la vacante

Vall d’Hebron Institute Oncology (VHIO) in Barcelona seeks a Postdoctoral Researcher to lead innovative research at the intersection of artificial intelligence, computational medical imaging, and multi-omics integration for precision oncology.

You will develop next-generation computational methods for quantitative imaging biomarkers and multimodal AI models that integrate imaging, molecular profiling, pathology and clinical data, to support early cancer detection, patient stratification and

Formación

• PhD in Computer Science, AI, Biomedical Engineering, Medical Imaging, or closely related discipline.

Responsabilidades

• Develop novel computational approaches for quantitative medical image analysis.
• Develop imaging biomarker tools.
• Apply artificial intelligence for precision oncology.
• Integrate multi-omics data combining imaging, genomics, pathology and clinical data.
• Predictive modelling for early cancer detection, patient prognosis and treatment response prediction.
• Develop reproducible research pipelines and software for translational cancer research.

Conocimientos

Python programming

AI research

Statistical modelling

Biomedical imaging

English proficiency

Educación

PhD in Computer Science / AI / Biomedical Engineering / Medical Imaging

Herramientas

Machine Learning frameworks (PyTorch, TensorFlow)

Descripción del empleo

Vall d’Hebron Institute Oncology (VHIO) in Barcelona seeks a Postdoctoral Researcher to lead innovative research at the intersection of artificial intelligence, computational medical imaging, and multi-omics integration for precision oncology.

You will develop next-generation computational methods for quantitative imaging biomarkers and multimodal AI models that integrate imaging, molecular profiling, pathology and clinical data, to support early cancer detection, patient stratification and