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# Post-doc ingénieur-e deep learning H/F

- **Company:** Emploi Services
- **Location:** Dieppe, France
- **Contract:** Temporary contract
- **Skills:** Airflow, Python (Programming Language), Machine Learning, NumPy, SQL Databases, Pytorch, Large Language Models, Deep Learning, Gitlab, Git, Pandas, Scikit Learn
- **Published:** July 30, 2026
- **Apply:** https://nostalentsnosemplois.auvergnerhonealpes.fr/candidat/offres/offre-d-emploi-ingenieur-de-recherche-en-deep-learning-h-f-auvergne-rhone-alpes-environnement-eau-cdd-16182504

## About the Role

Vous etecirc;tes titulaire d'un doctorat dans le domaine du deep learning appliqueteacute; etagrave; l'image.
Vous etecirc;tes familier avec les techniques du type Vision transformer et les approches multimodales (ex : ImageBind).
Vous etecirc;tes etagrave; l'aise avec le stack python scientifique (pandas, numpy, scikit learn, pytorch).
Connaissances appreteacute;cieteacute;es :
Tensorboard, mlflow, dagster, dbt
Technologies de base de donneteacute;es relationnelles (SQL)
git, gitlab
Vous disposez d'une aptitude au travail en eteacute;quipe.
Vous faites preuve de rigueur et disposez d'un sens de l'organisation.
Vous avez un esprit critique et vous etecirc;tes force de proposition.
Vous disposez de capaciteteacute;s reteacute;dactionnelles et vous avez un esprit de synthetegrave;se.
Vous faites preuve de curiositeteacute; et de creteacute;ativiteteacute;.
Vous souhaitez etecirc;tre acteur d'un monde qui change, rejoignez-nous !

## Description

La direction Energie Environnement, composeteacute;e de 120 ingeteacute;nieurs et chercheurs passionneteacute;s recherche un(e) Post-Doc talentueux(se) pour rejoindre l'eteacute;quipe IDPB en charge de la Base de Donneteacute;es Nationale des Betacirc;timents.
Votre retocirc;le sera de continuer le deteacute;veloppement de modetegrave;les multimodaux images (faetccedil;ade, aeteacute;rien et satellite) / donneteacute;es tabulaires (et potentiellement LLM) appliqueteacute;s aux betacirc;timents, issus d'un preteacute;ceteacute;dent post-doc.
Ce postdoc a pour objectif d'eteacute;tendre les travaux du post doc preteacute;ceteacute;dant :
Explorer les sujets algorithmiques sur l'entrainement multimodale et son exploitation dans le cadre de la preteacute;diction de donneteacute;es manquantes etagrave; partir d'images afin d'en ameteacute;liorer la performance. Et eteacute;tendre le contexte aux betacirc;timents tertiaires, dont le niveau de description est tretegrave;s faible.
Deteacute;velopper des modetegrave;les de betacirc;timents multimodaux. Les reteacute;sultats devront permettre etagrave; nos ingeteacute;nieurs et etagrave; nos utilisateurs de capitaliser diffeteacute;rentes modaliteteacute;s de donneteacute;es Magal betacirc;timentaire (tabulaire, image, texte...) pour les tetacirc;ches aval de machine learning telles que :
preteacute;diction de typologies de betacirc;timent (classification, clustering)
recherche et interaction avec la description du betacirc;timent en langage naturel
recherche par similariteteacute; (Retrieval Augmented Generation ou RAG)


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