Research engineer [F/M] for AI-driven molecular and spatial analysis of tumor cell plasticity

inria; France; On-site; EUR 27,000 - 33,000; Full time

Benefits offered by this job

Transport reimbursement

Leave: 7 weeks + RTT days

Teleworking after 6 months

Equipment provided

Training and development

Job summary

Inria Lyon's BioTiC team offers a two-year research engineer position focused on turning a differential network analysis prototype into a robust Python package. You will collaborate with AIMPACT partners to apply methods on biological networks, predict regulatory genes, and contribute to toolbox enhancements and documentation.

The role emphasizes bioinformatics, machine learning, and software development within cancer biology, with opportunities to publish and present at conferences.

Qualifications

• MSc degree or equivalent in computer science, mathematics, or related field.
• Experience applying computational methods to bioinformatics or software development is desirable.
• Strong programming skills in Python or R and ability to document and disseminate results.

Responsibilities

• Transform a prototype differential network analysis tool into a professional Python package.
• Apply differential network analysis on networks from AIMPACT partners.
• Predict genes and genetic interactions for further analysis by AIMPACT partners.

Skills

Software engineering

Statistics

Machine learning/AI

Explainability

Single-cell data analysis

Network inference

Data visualization

Python/R programming

Education

MSc degree in CS/Math or equivalent

Tools

Python

R

Git

Job description

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 Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 10 Nov 2026 - 00:00 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 38.5 Offer Starting Date 1 Mar 2027 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 2026-10598 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

A two-year research engineer position is available in team BioTiC at Inria Lyon. At BioTiC, we study cellular systems through computational models and bioinformatic data analysis, in order to better understand their organizational principles. In our team, we value working together, being innovative, and providing opportunities for professional and personal growth.

The position is within the framework of project AIMPACT, a collaboration between Magali Richard, Yuna Blum, Sophie Achard (CNRS), Anton Crombach (Inria), and Alex Petersen (Brigham Young University, Utah, USA). The overall goal of this project is to better understand tumor cell plasticity, that is to say the ability of cancer cells to dynamically reprogram their transcriptional programs in response to environmental cues. You will be advised by Anton Crombach , whilst working together with other members of the project. Y ou will be located at Inria’s La Doua site and you will have regular opportunities to visit partners in Grenoble and Rennes.

You will benefit from the expertise at BioTiC regarding bioinformatic data analysis and computational modelling of biological systems; and through AIMPACT’s partners you will profit from world‑class knowledge regarding statistics, machine learning and AI, and cancer biology. Overall, the project will foster your career in terms of building up cutting‑edge expertise on high-dimensional data analysis, network inference, statistics, machine learning and AI, and data visualization techniques – areas that are strongly demanded in academia and industry.

AIMPACT focuses on the identification of molecular mechanisms associated with tumor cell plasticity. Tumor cell plasticity refers to the ability of cancer cells to alter their transcriptional programs in response to environmental cues, enabling them to adapt and evade therapies. Unlike normal cells that have stable cell types, tumor cells can dynamically switch between molecular states, acquiring more aggressive features. This non‑genetic adaptability is orchestrated by epigenetic modifications, transcription factor activity, and gene regulatory networks (GRNs). Tumor plasticity has been widely observed across multiple cancers and here we study it in pancreatic ductal adenocarcinoma (PDAC), one of the most lethal malignancies. Despite recent advances, our ability is limited to predict and control tumor plasticity. Addressing this gap requires innovative AI methods that can integrate multi‑modal data, incorporate uncertainty, provide interpretable insights, and capture the dynamic nature of cellular state transitions in their spatial context—capabilities that lie beyond conventional approaches.

Your primary goal within the project will be to transform a prototype software for differential network analysis into a professional Python package. This will includ e, but is not limited to, developing novel visualization features , creating extensive documentation, preparing example notebooks, and identifying candidate regulatory processes for further analysis by AIMPACT’s partners . You will also have time to pursue additional initiatives, for instance designing and implementing novel analysis tools that build on the existing prototype. Naturally, w e are open to discuss other initiatives on a case‑by‑case basis.

The goal of this two‑year research engineer position is to provide and use cutting‑edge tools to better understand how drug tolerance manifests itself in gene regulatory processes. This means your main activities are:

• transform a prototype software for differential network analysis into a Python package
• apply differential network analysis on networks generated by AIMPACT’s partners
• predict genes and genetic interactions linked to drug‑tolerance for further analysis by our partners

Finally, you are strongly encouraged to disseminate your work through publications in international journals and by presenting it at national and international conferences.

The project requires skills in computer science, mathematics, and (cancer) biology. A successful candidate has experience in one or more of the following areas:software engineering, statistics and machine learning / AI, explainability, single‑cell data analysis, network inference, data visualization, programming in Python/R. Affinity with cancer biology and the challenge of cellular state transition in pancreatic cancer is considered a real advantage. Good oral and written communication skills in English are essential.

Specific Requirements

The applicant should have a strong basis in computer science/mathematics or similar field ( MSc degree or equivalent), ideally oriented toward bioinformatic data analysis and/or software development . An essential quality for this project is a keen interest to apply one’s computational skills to help answering biological questions. An interest in single‑cell technologies and network inference is considered a real asset, as is wanting to communicate and collaborate with ( computational ) biologists that study cancer.

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

from €2,692 gross per month

Selection process

Defence security: This position is likely to be assigned to a restricted area (ZRR), as defined in decree no. 2011-1425 relating to the protection of the nation's scientific and technical potential (PPST). Authorisation to access a zone is issued by the head of the establishment, following a favourable ministerial opinion, as defined in the decree of 03 July 2012 relating to the PPST. An unfavourable ministerial opinion for a post assigned to a ZRR would result in the recruitment being cancelled.