Post-Doctoral Research Visit F - M Causal Inference And Mechanistic Digital Twins For Individualized Adjuvant Treatment In Resected Lung Cancer H/F - INRIA

A propos d'Inria

Inria, l'institut national de recherche dans les sciences et technologies du numérique, est en appui de l'État pour les stratégies nationales de recherche et d'innovation du numérique en tant qu'Agence de programmes. Inria mène plus de 300 projets de recherche et d'innovation avec ses 3500 scientifiques, ingénieurs et personnels d'appui, en partenariat avec les universités et l'écosystème numérique (entreprises, entrepreneurs, acteurs publics). Ensemble, nous explorons des domaines clés comme l'intelligence artificielle, la cybersécurité, l'informatique quantique, le Cloud, la transformation numérique de la santé, les jumeaux numériques ou encore les technologies numériques pour la défense. Nous construisons des solutions concrètes telles que des logiciels, des startups technologiques, des partenariats avec les entreprises du tissu national et des formations de pointe. Notre objectif : l'impact scientifique, technologique et industriel au service de la souveraineté numérique de la France.

Post-Doctoral Research Visit F/M Causal inference and mechanistic digital twins for individualized adjuvant treatment in resected lung cancer
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD

Niveau de diplôme exigé : Thèse ou équivalent

Fonction : Post-Doctorant

Niveau d'expérience souhaité : Jusqu'à 3 ans

A propos du centre ou de la direction fonctionnelle

Inria is the French National Institute for Research in Digital Science, of which the Inria Côte d'Azur University Center is a part. With strong expertise in computer science and applied mathematics, the research projects of the Inria Côte d'Azur University Center cover all aspects of digital science and technology and generate innovation. Based mainly in Sophia Antipolis, but also in Nice and Montpellier, it brings together 47 research teams and nine support services. It is active in the fields of artificial intelligence, data science, IT system security, robotics, network engineering, natural risk prevention, ecological transition, digital biology, computational neuroscience, health data, and more. The Inria Center at Université Côte d'Azur is a major player in terms of scientific excellence, thanks to the results it has achieved and its collaborations at both European and international level.

Contexte et atouts du poste

This position is funded by the RHU LUCA-pi project (Recherche Hospitalo-Universitaire, France 2030), dedicated to personalized medicine in early-stage non-small cell lung cancer (NSCLC). LUCA-pi brings together clinical, biological and computational partners around a large retrospective cohort (LUCA-pi RETRO) and a prospective cohort of patients treated with surgery.

The postdoc will join the COMPO team (COMPutational pharmacology and clinical Oncology, Inria - Inserm - Aix-Marseille Université), located at the Cancer Research Center of Marseille (CRCM). Within LUCA-pi, COMPO develops a mechanistic model of metastatic relapse - a digital twin - that predicts each patient's risk of relapse after surgery. The postdoc will work closely with the PhD student building this model, and with the project's clinicians.

Mission confiée

Adjuvant therapies (chemotherapy, immunotherapy, targeted therapy) are prescribed according to clinical criteria, so their real-world effect cannot be read directly from observational data because of confounding by indication, immortal time bias and lack of positivity. Combining causal inference with mechanistic modeling is still largely unexplored.

The goal of the postdoc is to add a causal layer to the LUCA-pi digital twin, along two lines:

- Applied: estimate the causal effect of adjuvant treatment on metastatic relapse by emulating a target trial on LUCA-pi RETRO (clone-censor-weighting; risk differences and RMST, accounting for competing risks). Average effects will be estimated with robust methods (AIPW/TMLE) and heterogeneous effects with causal survival forests and meta-learners, then compared with published randomized trials (LACE, IMpower010, ADAURA).
- Methodological: connect causal inference and mechanistic modeling with calibration of treatment-effect parameters of nonlinear mixed-effects models under confounding, hybrid estimators using the mechanistic model as outcome model, and a semi-synthetic benchmark with known counterfactuals generated by the digital twin.

Principales activités

- Audit and curate the clinical data (treatment dates, confounders, biomarkers).
- Design and implement causal survival analyses, including sensitivity analyses for unmeasured confounding.
- Develop and benchmark new methods combining mechanistic and causal approaches.
- Collaborate with the PhD student and the clinicians of the LUCA-pi consortium.
- Publish the results and present them at international conferences.

Compétences

- Strong background in causal inference (potential outcomes, propensity scores, doubly-robust estimation) and survival analysis.
- Proficiency in R and/or Python.
- Interest in dynamical/mechanistic models; experience with mixed-effects models is a plus.
- Interest in clinical applications; good communication skills in English (French not required).

Avantages

- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage

Rémunération

Gross Salary: 2788 € per month