PhD Position F/M Cifre PhD - Mathematical and statistical modeling of cfDNA size fragments for diagnosis and prediction in oncology - INRIA
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description du poste

Contexte et atouts du poste

This Cifre PhD position will take place between Adelis technologies (Toulouse) and the Inria-Inserm team COMPO (COMputational Pharmacology in Oncology), located in the La Timone health campus. The COMPO team comprises mathematicians, data scientists, pharmacists and clinicians and is a unique multidisciplinary environment focused on developing novel computational tools for decision-making in clinical oncology.

Mission confiée

Background

Liquid biopsy has established itself as a powerful tool for the early detection of cancer and the diagnosis, prognosis and treatment monitoring in a wide range of cancer types [1]. The BIAbooster technology from Adelis allows precise quantification of the size of cell free DNA fragments from plasma samples, establishing size distributions over a wide range of base pairs (part of the fragmentome). In the SChISM (Size Cfdna Immunotherapies Signature Monitoring, N = 334 patients) study led by Pr S. Salas (APHM and COMPO), we have demonstrated that features derived from these distributions were predictive of response to immunotherapy as univariable biomarkers [2, 3] or integrated within multivariable machine learning predictive models.

One of the main interest of such non-invasive biomarkers is for monitoring the response during treatment. We have developed a first mechanistic model of the longitudinal data collected during SChiSM that demonstrated added value for prediction of progression [4].

Objectives

  • At Adelis, develop advanced signal processing methods to improve the information extracted from the cfDNA fragment size distributions
  • Develop mechanistic models of the dynamics of the cfDNA size distributions, coupled with tumor and immune variables
  • Implement a clinical decision tool for adaptive therapeutic decision

    • Methodology

  • Optimization of scalar or functional metrics derived from the cfDNA size distributions
  • Mathematical modeling of the system dynamics, first using ordinary differential equations, then with size-structured partial differential equations
  • Statistical modeling of the inter-individual variability through mixed-effects modeling
  • Joint modeling for association with time-to-event outcomes (progression-free or overall survival)

    • References:

  • Computational modeling for circulating cell-free DNA in clinical oncology
    L. Nguyen-Phuong, S. Salas, S. Benzekry
    JCO Clinical Cancer Informatics, 2025, 9
  • The SChISM study: Cell-free DNA size profiles as predictors of progression in advanced carcinoma treated with immune-checkpoint inhibitors
    Linh Nguyen Phuong, Frederic Fina, Laurent Greillier, Pascale Tomasini, Jean-Laurent Deville, Romain Zakrasjek, Lucie Della-Negra, Audrey Boutonnet, Frédéric Ginot, Jean-Charles Garcia, Sébastien Benzekry, Sébastien Salas
    under review, 2025
  • Long cell-free DNA fragments predict early-progression in patients with advanced or metastatic cancer treated with immune-checkpoint inhibition.
    Sébastien Salas, Linh Nguyen Phuong, Jean-Charles Garcia, Laurent Greillier, Caroline Gaudy-Marqueste, Jean-Laurent Deville, Audrey Boutonnet, Frédéric Ginot, Frédéric Fina, Sébastien Benzekry
    ASCO, 2024

  • Principales activités

    Main activities : Statistical data analysis Signal processing Mathematical modeling Statistical modeling (nonlinear mixed-effects modeling) Machine learning Programming Reporting: writing scientific papers, oral communications

    Additional activities :

    Review the literature Test and enhance the codebase Presentation to a non-technical audience Conceive apps for biomedical users (e.g. Shiny apps)

    • Compétences

    Technical skills and level required :

  • Excellent programming skills in a scripting language (R/python)
  • Strong background in mathematical modeling
  • Strong background in statistics and machine learning
  • Hands-on experience with real-world biomedical data analysis
  • Experience with nonlinear mixed-effects modeling is a plus
  • Experience in signal processing is a plus

    • 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
  • Contribution to mutual insurance (subject to conditions)

    • Rémunération

    Duration: 36 months
    Location: Sophia Antipolis, France
    Gross Salary per month: 2200€ and 2300€ from 2026.

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