Precision Adaptive Thoracic Radiotherapy Scientist (AI)

Italian Ministry of Education, University and Research

Italia

On-site

EUR 45,000 - 65,000

Full time

2 days ago
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Job summary

Università Campus Bio-Medico di Roma in Italy invites applications for a Researcher Profile Leading Researcher (R4) in radiotherapy. The role focuses on precision and adaptive radiotherapy for thoracic malignancies, with emphasis on locally advanced NSCLC and oligometastatic settings, advancing translational clinical research within a multidisciplinary unit.

The successful candidate will identify and validate quantitative imaging biomarkers, integrate imaging with clinical and molecular data to

Responsibilities

  • Identification and validation of quantitative biomarkers from imaging such as CT, PET/CT and functional imaging.
  • Integration of imaging data with clinical, pathological, molecular and dosimetric information to develop predictive models of response, control and toxicity.
  • Development and validation of machine learning, deep learning and explainable AI models with focus on robustness and clinical interpretability.
  • Development and evaluation of adaptive radiotherapy strategies guided by anatomical, functional and biological changes during treatment.
  • Investigation of combining radiotherapy with immunotherapy and targeted therapies to tailor strategies across thoracic disease settings.
  • Methodologies to optimize patient selection, dose and treatment volumes to maximize therapeutic ratio and minimize toxicity.

Job description

Università Campus Bio-Medico di Roma in Italy invites applications for a Researcher Profile Leading Researcher (R4) in radiotherapy. The role focuses on precision and adaptive radiotherapy for thoracic malignancies, with emphasis on locally advanced NSCLC and oligometastatic settings, advancing translational clinical research within a multidisciplinary unit.

The successful candidate will identify and validate quantitative imaging biomarkers, integrate imaging with clinical and molecular data to

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