Phd Position F - M Cifre Phd - Mathematical And Statistical Modeling Of Cfdna Size Fragments For Diagnosis And Prediction In Oncology H/F INRIA

PhD Position F/M Cifre PhD - Mathematical and statistical modeling of cfDNA size fragments for diagnosis and prediction in oncology
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD

Niveau de diplôme exigé : Bac +5 ou équivalent

Fonction : Doctorant

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

ThisCifre PhD position will take place between (Toulouse) andthe Inria-Inserm team COMPO (COMputational Pharmacology in Oncology), located in the La Timone health campus. The COMPO teamcomprises 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:
- L. Nguyen-Phuong, S. Salas,S. Benzekry
JCO Clinical Cancer Informatics, 2025, 9
- 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
- Linh Nguyen Phuong, Frederic Fina, Romain Zakrajsek, Lucie Della-Negra, Pascale Tomasini, Jean-Laurent Deville, Laurent Greillier, Caroline Gaudy-Marqueste, Audrey Boutonnet, Frédéric Ginot, Jean-Charles Garcia, Sébastien Salas, Sébastien Benzekry
PAGE 2025

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 inmathematical 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€ (2025) and 2300€ from 2026.