An Integrated Monte Carlo and Artificial Intelligence Framework for Response Prediction in Targeted Radionuclide Therapy

This project aims, initially, to develop an approach based on Monte Carlo simulation to generate realistic SPECT images. These simulations will complement experimental data and improve quantification methods by incorporating detailed modelling of physical interactions, as well as correction and reconstruction processes.

In a second phase, the project will focus on the large-scale integration of heterogeneous pre-therapeutic data. This will include imaging parameters (radiomics, SUV, tumour volumes), as well as clinical and biological data. Methods for structuring, harmonising and multimodal fusion will be implemented to build a coherent, rich and usable database. On this basis, artificial intelligence algorithms will be developed to train robust predictive models, combining simulated and real data.

The final aim of this PhD is to identify reliable predictive biomarkers, to improve the prediction of therapeutic response, and to better link pre-treatment characteristics to dose distributions and biological effects.

Applicant profile

This work is intended to be transdisciplinary, involving clinicians, IT specialists, and medical physicists. Applicants must hold at least an upper second-class degree or equivalent qualification in a relevant subject, such as computer science, applied mathematics, biomedical engineering or medical physics. A Master's degree in a relevant discipline and additional research experience would be advantageous. Candidates should be fluent in English or French.

Personal characteristics:

• Curiosity, independence, initiative and scientific rigour;
• Interpersonal skills and professional discretion (work in a hospital environment).

Application

Applicants are invited to submit their application to the PhD main supervisors. Application must contain the following documents:

• CV;
• Cover letter;
• At least one reference letter.

Funding Notes

Salary (gross): 2300 € per month