Refining generative models for B-cells recombination and mutation.

Inria, the French national research institute for the digital sciences; France; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

A leading research institute in France seeks a motivated intern to join the COMPO team in Marseille. The role involves developing mathematical models for oncology decision-making. Candidates should possess strong skills in statistics and programming (Python/C++). The internship offers an attractive stipend, 38.5 hours/week, and opportunities for professional development. Teleworking is possible after 6 months. Interested applicants should apply by January 2026, with the internship starting in early 2025.

Prestations

Partial reimbursement of public transport costs

7 weeks of annual leave

10 extra days off due to RTT

Possibility of teleworking after 6 months

Flexible working hours

Access to professional equipment

Social, cultural, and sports events

Access to vocational training

Social security coverage

Qualifications

• Motivated candidate with strong skills in probability and statistics.
• Programming skills in Python and C/C++ are essential.
• Interest in immunology and cancer applications is an advantage.

Responsabilités

• Conduct literature reviews and frame hypotheses.
• Analyze data and create visualizations.
• Communicate results in team meetings.

Connaissances

Probability

Statistics

Scientific computing

Python programming

C/C++ programming

Formation

Background in bioinformatics, applied mathematics or physics

Description du poste

Inria, the French national research institute for the digital sciences

Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1) Country France Application Deadline 19 Jan 2026 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 38.5 Offer Starting Date 1 Feb 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 2025-09664 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

General Information
Duration: 5-6 month
Location: Marseille (on site)
Internship start: January to April
Internship stipend : ~670€ / month

COMPO team

The internship will take place within the COMPO team on the Timone Campus in Marseille. The ambition of the COMPO Inria-Inserm joint project-team is to develop novel mathematical models integrating data available in clinical oncology (from clinical trials and routine care), in order to provide decision-making tools to oncologists. To achieve this, the team uniquely
gathers mathematicians, pharmacologists and medical oncologists. It is integrated in the Center of Cancer Research of Marseille (Inserm U1068, CNRS UMR7258, Aix-Marseille Université UM105, Institut Paoli-Calmettes) and located in the La Timone Health Science campus of the University Hospitals of Marseille (AP-HM), close to the INCa-labeled center for early phase clinical trials (CLIP2). This joint project-team, built on strong expertise in mathematical modeling, pharmacometrics and experimental and clinical oncology, is committed to develop novel methodologies combining mechanistic and statistical modeling to be ultimately applied at bedside.

The work will take part along with the resumption of development of the IGoR software driven by several Inria senior software engineers (from Inria-Sophia SED) through several coding sprints to which the trainee isstrongly encouraged to attend.

Context and Objectives of the Internship
Motivation : The adaptive immune system comprises antigen-specific lymphocytes, namely B
and T lymphocytes. Each of these lymphocytes carries numerous copies of a unique receptor T
cell receptors (TCRs) for T lymphocytes and B cell receptors (BCRs) for B lymphocytes. The
nucleotide sequence of these receptors is not contained in the individual germinal DNA but is
randomly generated through the process of VDJ recombination. This stochastic germline DNA
editing process combines a combinatorial choice among V, D and J gene families, together with
random nucleotide deletions and insertions to generate an enormous diversity of T and B cells,
each carrying their specific TCR and BCR. It is this randomly generated diverse set of
lymphocytes, mostly created prior to birth, that constitutes the immune repertoire, and enables
the specific recognition of virtually any pathogen throughout an individual’s lifetime. Owing to
this complexity, building quantitative frameworks to extract meaningful information from
high-throughput Adaptive Immune Receptor Repertoire (AIRR) sequencing experiments is at the
cornerstone of understanding the adaptive immune system in health and disease..
Internship Projects : In the past we have successfully built mechanistic statistical generative
models to the probability of generation (Pgen) of nucleotide sequences of V(D)J-recombined
nucleotide sequences and somatic mutations introduced by affinity maturation using the IGoR
software. While the inferred models have been successfully applied to predict receptor sharing
statistics, detect expanded clones or detect B-cell lineages to name a few, they fall short of
describing observed phenomena such as:
- Tandem D segments and longer insertion profiles: some experiments suggested that in a minority
of recombination events two D-gene segments may be included in the resulting sequence. Owing
to the short length of D genes and random deletions occuring during recombination such tandem
D insertions are difficult to tell apart from random nucleotide insertions. Using generative models
of VDJ recombination allowing only for a single D gene segment we have previously quantitatively
demonstrated that insertions alone were not sufficient to reproduce the number of sequences displaying tandem D compatible sequences. The development of generative models accommodating for such tandem D insertions would shed new light on the differences between T and B cell VDJ recombination while providing more accurate predictions for downstream use.

- Population-level allelic variability in VDJ genes : researchers in computational immunology have
long relied on curated lists of allelic variants e.g. from the IMGT database. However with the
increased availability of repertoire sequencing data it has become evident that current sets are
incomplete and unrepresentative of the degree of polymorphism and diversity in human and
animal populations, while containing many spurious allele for a given individual. While some
solutions have been proposed by the community to infer alleles from repertoire sequencing data,
these solutions only address V gene polymorphism. Adapting such approaches to IGoR’s
probabilistic framework, coupled with a previously developped haplotype inference strategy,
could allow inference of germline variants even in the short D and J genes.

Keywords
Adaptive immune system; B cells; VDJ recombination; Somatic Hypermutations (SHMs);
Mutational Signatures; Generative Models; statistical data analysis

Main activities (5 maximum) :

• Literature review & hypothesis framing
• Data analysis &Visualization
• Communication of the results in team meetings

Desired Skills
We are looking for a motivated candidate with skills in probability, statistics, and scientific
computing coming from a bio-informatics, applied mathematics or physics background.
Knowledge of biology is not required but valued, and an interest in applications to immunology
and cancer is expected.
Programming skills in Python and C/C++ languages are necessary.

Languages FRENCH Level Basic

Languages ENGLISH Level Good

Additional Information

• 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