PhD Position F/M [Numetab project] High-dimensional data analysis in the framework of survival modelling in presence of competing risks.

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Offre n°2026-10166

PhD Position F/M [Numetab project] High-dimensional data analysis in the framework of survival modelling in presence of competing risks.

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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

The Inria University of Lille centre, created in 2008, employs 360 people including 305 scientists in 15 research teams. Recognised for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria University of Lille centre pursues a close relationship with large companies and SMEs. By promoting synergies between researchers and industrialists, Inria participates in the transfer of skills and expertise in digital technologies and provides access to the best European and international research for the benefit of innovation and companies, particularly in the region.

For more than 10 years, the Inria University of Lille centre has been located at the heart of Lille's university and scientific ecosystem, as well as at the heart of Frenchtech, with a technology showroom based on Avenue de Bretagne in Lille, on the EuraTechnologies site of economic excellence dedicated to information and communication technologies (ICT).

Contexte et atouts du poste

The PhD candidate will join both the Datavers team based in the Inria center at the University of Lille (France) and the METRICS unit research based in the Faculty of Medicine at the University of Lille.

Inria Datavers team is specialised in statistical learning and her members also belong either to Paul Painlevé laboratory or METRICS.

Research of Paul Painlevé laboratory covers a broad spectrum of mathematical research.

METRICS is a multidisciplinary public health research team that brings together clinicians and methodologists in the fields of ergonomics, biostatistics, medical informatics, data science and health economics.

Mission confiée

The aim of the PhD thesis is to develop a new statistical method for variable selection in the context of survival analysis, with competing risks, where measurements are repeated over time on thousands of variables simultaneously. This PhD project is funded by the Numetab cross disciplinary project (Numerical transition in Obesity and Metabolic Research, PI: Pr. Pattou and Pr. Marot).

The application will be to identify new omics markers (transcriptomics, metabolomics, proteomics) for predictive purposes in order to adapt patients’ treatment (Precision Health). The originality of the statistical approach consists in simultaneously addressing three scientific challenges: i) high-dimensional analysis (more variables than individuals), ii) analysis of competing risks in the context of survival models and iii) analysis of longitudinal data (repeated measurements on the same individuals).

Results are expected both in terms of biostatistical methodology and software to provide a clinical decision support tool.

Principales activités

The main objective is to develop a statistical method for selecting variables in a context of survival prediction in the presence of competing risks.

Secondary objectives are:

to improve the search for biomarkers in analyses with repeated omics data to develop a decision-support software tool that can be generic and can be used in any context of high-dimensional data analysis with survival models in the presence of competing risks.

PhD candidates who want to understand the concepts necessary for this PhD can read the following references:

• related to statistics

[1] Fine and Gray (1999) A proportional hazards model for the subdistribution of a competing risk. Journal of the American statistical association, 94(446):496–509.

[2] Chi and Ibrahim (2006) Joint models for multivariate longitudinal and multivariate survival data. Biometrics, 62(2):432–445.

[3] Binder, Allignol, Schumacher, and Beyersmann (2009) Boosting for high-dimensional time-to-event data with competing risks. Bioinformatics, 25(7):890–896.

• related to another application which motivated the PhD subject (proteomics data analysis)

[4] Heyse, Vandewalle, Marot, Amouyel, Bauters, and Pinet (2023) Identification of patient subtypes based on protein expression for prediction of heart failure after myocardial infarction. Iscience, 26(3).

Compétences

The candidate must hold a MSc in Biostatistics.

Technical skills and level required :

Proficiency in R and at least one scripting language (e.g. python)

In-depth knowledge of statistical learning to handle high-dimensional data

Basic knowledge of biology (molecular and cellular biology, genomics and genetics)

Other valued appreciated : creativity, independence, team working and communication skills

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 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

€2,300 gross per month

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Informations générales

Thème/Domaine : Optimisation, apprentissage et méthodes statistiques

Statistiques (Big data) (BAP E)

Ville : Villeneuve d'Ascq

Centre Inria : Centre Inria de l'Université de Lille

Date de prise de fonction souhaitée : 2027-01-01

Durée de contrat : 3 ans

Date limite pour postuler : 2026-12-12

Attention: Les candidatures doivent être déposées en ligne sur le site Inria. Le traitement des candidatures adressées par d'autres canaux n'est pas garanti.

Consignes pour postuler

Please send us your CV and cover letter.

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 potentiel scientifique et technique de la nation (PPST). L’autorisation d’accès à une zone est délivrée par le chef d’établissement, après avis ministériel favorable, tel que défini dans l’arrêté du 03 juillet 2012, relatif à la PPST. Un avis ministériel défavorable pour un poste affecté dans une ZRR aurait pour conséquence l’annulation du recrutement.

Politique de recrutement :

Dans le cadre de sa politique diversité, tous les postes Inria sont accessibles aux personnes en situation de handicap.

Contacts

Équipe Inria : DATAVERS

Directeur de thèse :

Marot Guillemette /

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.

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