Machine Learning From Cfdna Size Fragments for Diagnosis and Prediction of Response to Immunotherapy in Oncology

_Le descriptif de l’offre ci-dessous est en Anglais_

**Niveau de diplôme exigé**: Bac + 4 ou équivalent

**Fonction**: Stagiaire de l'ingénierie

**A propos du centre ou de la direction fonctionnelle**:
The Inria center at Université Côte d'Azur includes 42 research teams and 9 support services. The center’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM...), but also with the regional economic players.

With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d'Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.

**Contexte et atouts du poste**:
This engineering internship position will take place in the environment of the Inria-Inserm team COMPO (COMputational Pharmacology in Oncology), located in the La Timone health campus. The team is composed of 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**:
Liquid biopsy has established itself as a powerful tool for the early detection of cancer and the diagnosis

diagnosis, prognosis and treatment monitoring in a wide range of cancer types. As part of the

SChISM (Size Cfdna Immunotherapies Signature Monitoring) project, the COMPO team is studying the

fragmentome, i.e. the size distribution of circulating cell-free DNA fragments, and has obtained significant

from individual markers (Salas et al., ASCO 2024, ESMO 2024).

The aim of this internship is to evaluate, develop and implement machine learning analyses to develop

analyses to develop two predictive algorithms by combining simple markers into multivariate

multivariate models: one for screening (cancer versus healthy) and the other for resistance to2

immunotherapy. The analyses will involve two stages: variable selection and modelling,

using learning algorithms evaluated by controlling optimism (overlearning).

**References**:

- **Computational modeling for circulating cell-free DNA in clinical oncology**
L. Nguyen-Phuong, S. Salas, **S. Benzekry**:

- under minor revision_, hal 2024
- Circulating cell-free DNA size distribution as a prediction marker for early progression undergoing immune checkpoint inhibitors
L. Nguyen Phuong, F. Fina, L. Greillier, C. Gaudy-Marqueste, J.L. Deville, J.C. Garcia, S. Salas, **S. Benzekry**:

- PAGE_, 32, Abstr 11111, Poster, 2024
- Long circulating-free DNA fragments predict early-progression (EP) and progression-free survival (PFS) in advanced carcinoma treated with immune-checkpoint inhibition (ICI): A new biomarker.
Salas, S., Nguyen-Phuong, L., Ginot, F., Greillier, L., Tomasini, P., Boutonnet, A., Deville, J.L., Fina, F. and **Benzekry, S**.
- ESMO, Ann. Oncol.,_ 35, S270, Poster, 2024.

**Principales activités**:
**Main activities**:

- Supervised machine learning
- Feature selection
- Biostatistics
- Craft synthetic reports and publication-ready figures

**Additional activities**:

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

**Compétences**:
Technical skills and level required:

- Excellent programming skills in a scripting language (preference for R)
- Strong background in statistics and machine learning
- Hands-on experience with real-world data analysis

**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

**Rémunération**:
Traineeship grant depending on attendance hours.

**Informations générales**:

- **Thème/Domaine**: Neurosciences et médecine numériques
- **Ville**: Marseille
- **Centre Inria**: Centre Inria d'Université Côte d'Azur
- **Date de prise de fonction souhaitée**: 2025-02-01
- **Durée de contrat**: 6 mois
- **Date limite pour postuler**: 2025-01-31

**Consignes pour postuler**:
**Sécurité défense**:
Ce poste est susceptible d’être affecté dans une zone à régime restrictif (ZRR), telle que définie dans le décret n°2011-1425 relatif à la protection du potenti