4 meilleures offres (deep learning engineer, bretagne) (à pourvoir)

Scientific engineer in Bioinformatics (2 years): New Classification of Enzymatic Functions and Datasets for Hierarchical Annotation Using Deep Learning
Inria —Rennes (35)
- À partir de 2 695 € par mois
- Anglais
- Master
- Machine learning
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Scientific engineer in Bioinformatics (2 years): New Classification of Enzymatic Functions and Datasets for Hierarchical Annotation Using Deep Learning

Inria -
Rennes (35)

Soumettre votre candidature

Détails de l'emploi

CDD
À partir de 2 695 € par mois

Avantages

Qualifications

Bio-informatique
Go
UNIX
Git
Anglais
Master
Machine learning
Développement logiciel
Linux
Python

Description complète du poste

Le descriptif de l’offre ci-dessous est en Anglais

Type de contrat : CDD

Niveau de diplôme exigé : Bac + 5 ou équivalent

Autre diplôme apprécié : Master's degree (MSc) or Engineering degree in Bioinformatics, Computational Biology, Computational Biology, Molecular Biology, Biotechnology, Computer Science, or a related discipline.

Fonction : Ingénieur scientifique contractuel

A propos du centre ou de la direction fonctionnelle

The Inria center at the University of Rennes is one of eight Inria centers and has more than thirty research teams. The Inria center is a major and recognized player in the field of digital sciences. It is at the heart of a rich ecosystem of R&D and innovation, including highly innovative SMEs, large industrial groups, competitiveness clusters, research and higher education institutions, centers of excellence, and technological research institutes.

Contexte et atouts du poste

Large language models, such as those powering ChatGPT, have transformed natural language processing and the analysis of complex sequential data. In biology, protein sequences can be viewed as a language, opening new perspectives for functional annotation.

The ECxit project (Exiting the EC Classification for Better Enzyme Annotation by Deep Learning), an Inria Exploratory Action led by François Coste, focuses on enzyme function annotation. By moving beyond the traditional EC classification, it aims to develop a novel deep learning-based annotation framework built on a redesigned hierarchical classification of enzymatic functions, enabling accurate predictions directly from amino acid sequences and ultimately improving genome annotation.

The project is hosted within the Machine Learning axis of the new Bioinformatics research team BioGraphs (formerly Dyliss) at the Inria Centre at Rennes University and the IRISA research laboratory. It benefits from the Genouest platform and from close collaborations with research groups in bioinformatics, biology, and health sciences.

Mission confiée

With the support of researchers from the BioGraphs team, the recruited person will contribute to the design and development of a novel framework for enzyme function annotation based on deep learning and protein language models.

The recruited person will be involved in the development of a new hierarchical classification of enzymatic functions, the construction of reference datasets and benchmarks, the evaluation of state-of-the-art prediction methods, and the deployment of a new annotation tool for the biological community.

Principales activités

Main activities:

Design and build a novel hierarchical classification of enzymatic functions by integrating information from major biological knowledge bases, including GO, EC, CAZy, Rhea, Reactome, BioCyc, and KEGG.
Develop a high-quality benchmark dataset for training and evaluating machine learning models for enzyme function prediction.
Evaluate state-of-the-art deep learning and protein language model approaches on the proposed benchmark in collaboration with machine learning researchers.
Construct a comprehensive reference dataset of enzyme functional annotations for large-scale model training.
Contribute to the development, evaluation, and deployment of a next-generation enzyme annotation tool based on deep learning approaches.

Additional Activities:

Contribute to scientific publications, technical reports, and software documentation.
Present results and project progress during team meetings, workshops, and scientific events.
Interact with biological end users and contribute to the dissemination and adoption of the developed tools.

Compétences

Technical skills and level required :

Good knowledge of bioinformatics, computational biology, molecular biology, or biological sequence analysis.
Knowledge of enzyme biology, enzymology, metabolism, and protein function annotation.
Experience with public biological resources such as GO, EC, KEGG, Reactome, Rhea, BioCyc, UniProt, or CAZy.
Familiarity with ontology-based data representation and annotation frameworks.
Ability to analyze, curate, integrate, and structure heterogeneous biological annotations from multiple data sources.
Experience with Python and scientific data processing.
Experience with Linux/Unix environments and software development best practices.
Experience with version control systems (Git) and collaborative software development.

Other appreciated qualifications:

Experience in biological data curation or annotation.
Experience in benchmarking biological datasets and evaluating prediction methods.
Contributions to scientific publications, databases, or open-source bioinformatics software.
Basic understanding of machine learning concepts and their application to biological data.

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

monthly gross salary from 2695 euros according to diploma and experience

Informations générales

Thème/Domaine : Biologie numérique
Biologie et santé, Sciences de la vie et de la terre (BAP E)
Ville : Rennes
Centre Inria : Centre Inria de l'Université de Rennes
Date de prise de fonction souhaitée : 2026-11-01
Durée de contrat : 2 ans
Date limite pour postuler : 2026-07-20

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 submit online : your resume, cover letter and letters of recommendation eventually

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 : BIOGRAPHS
Recruteur :
Coste Francois / [email protected]

L'essentiel pour réussir

The successful candidate should be interested in enzyme biology, bioinformatics, and biological data integration, and motivated by the development of high-quality resources for enzyme function annotation.

Essential qualities include:

Strong interest in bioinformatics and biological databases.
Interest in enzyme biology and functional annotation of proteins.
Ability to analyze complex biological data and propose practical solutions.
Curiosity, autonomy, and willingness to learn new concepts and methods.
Ability to work collaboratively in a multidisciplinary research environment.
Scientific rigor and attention to data quality, annotation reliability, and reproducibility.
Good communication skills and the ability to interact with both computational and biological scientists.
Interest in developing resources and tools for the biological community.

A propos d'Inria

Inria est l’institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l’interface d’autres disciplines. L’institut fait appel à de nombreux talents dans plus d’une quarantaine de métiers différents. 900 personnels d’appui à la recherche et à l’innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'eﬀorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.

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Scientific engineer in Bioinformatics (2 years): New Classification of Enzymatic Functions and Datasets for Hierarchical Annotation Using Deep Learning

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Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : deep learning engineer (bretagne)

A propos du centre ou de la direction fonctionnelle

Contexte et atouts du poste

Mission confiée

Principales activités

Compétences

Avantages

Rémunération

Informations générales

Consignes pour postuler

Contacts

L'essentiel pour réussir

A propos d'Inria

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