Post-Doctoral Research Visit F/M Causal inference and mechanistic digital twins for individualized adjuvant treatment in resected lung cancer

Post-Doctoral Research Visit F/M Causal inference and mechanistic digital twins for individualized adjuvant treatment in resected lung cancer Download job offer in PDF format Contract type : Fixed-term contract Level of qualifications required : PhD or equivalent Fonction : Post-Doctoral Research Visit Level of experience : Up to 3 years About the research centre or Inria department 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. Context 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. Assignment 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. Main activities • 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. Skills • 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). Benefits package • 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 Remuneration Gross Salary: 2788 € per month Apply for this position Share • Facebook • Linkedin • Twitter • Email General Information • Theme/Domain : Computational Neuroscience and Medicine Statistics (Big data) (BAP E) • Town/city : Marseille • Inria Center : Centre Inria d'Université Côte d'Azur • Starting date : 2027-01-01 • Duration of contract : 2 years • Deadline to apply : 2026-11-28 Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed. Instruction to apply Defence Security : This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment. Recruitment Policy : As part of its diversity policy, all Inria positions are accessible to people with disabilities. Contacts • Inria Team : COMPO • Recruiter : Benzekry Sebastien / Sebastien.Benzekry@inria.fr The keys to success PhD in biostatistics, statistics, machine learning or applied mathematics. Prior experience in causal inference or survival analysis is expected. About Inria Inria, the French national institute for research in digital science and technology, supports the French government in national research and innovation strategies in the digital field, acting as Digital Programs Agency. Inria leads over 300 research and innovation projects with its 3,500 scientists, engineers, and support staff, in partnership with universities and the digital ecosystem (businesses, entrepreneurs, and public stakeholders). Together, we explore strategic fields such as artificial intelligence, cybersecurity, quantum computing, cloud technologies, digital transformation in healthcare, digital twins, and digital technologies for defence. We develop practical solutions such as software, tech startups, partnerships with national companies, and cutting-edge training programmes. Our goal is to drive scientific, technological, and industrial excellence to ensure France’s digital sovereignty.