Stage 2025 - Machine Learning et simulation de systĂšmes dynamiques (All Gender)

Issy les Moulineaux

Airbus

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Job Description:

Et si votre aventure professionnelle commençait avec Airbus !

Vous recherchez un stage de fin d’annĂ©e ou intĂ©grĂ© dans une annĂ©e de cĂ©sure vous permettant de valider votre diplĂŽme? 

Nous vous proposons de travailler dans une entreprise leader mondial dans son domaine, tournĂ©e vers le digital, Ă  la pointe de la recherche et de l’innovation!

Une offre de stage intitulĂ©e « Stage 2025- Machine Learning et simulation de systĂšmes dynamiques (All Gender) » vient de s'ouvrir au sein de Airbus SAS sur son site d’Issy-Les-Moulineaux (France). Vous rejoindrez le dĂ©partement de Central R&T en charge de la modĂ©lisation physique et des mathĂ©matiques appliquĂ©es.

Votre stage consistera Ă  explorer et dĂ©velopper des approches “hybrides” combinant la simulation physique temporelle de systĂšmes dynamiques avec des techniques avancĂ©es de Machine Learning. La simulation de systĂšmes dynamiques, qu’il s’agisse des vibrations d’un hĂ©licoptĂšre ou de l’écoulement fluide autour d’une aile, reste en effet particuliĂšrement coĂ»teuse numĂ©riquement. Une telle association permettrait de rĂ©duire ce coĂ»t et d’envisager Ă  plus long terme l’optimisation poussĂ©e de grandes structures. 

Durant ce stage, l’attention sera portĂ©e sur l’analyse dynamique transitoire de composants aĂ©ronautiques et sur la façon dont une stratĂ©gie de modĂ©lisation multi-fidĂ©litĂ© peut ĂȘtre mise en place, alimentĂ©e par des outils haute-fidĂ©litĂ© (tels que la mĂ©thode des Ă©lĂ©ments finis) et par des mĂ©thodes d’apprentissage Ă  la prĂ©cision variable mais adaptable suivant le besoin.

Un travail sur la quantification des incertitudes (pour prĂ©ciser le potentiel des outils mis en place) et sur les mĂ©thodes de rĂ©duction de modĂšle (pour mieux gĂ©rer la complexitĂ© des systĂšmes) permettra in fine d’échafauder une stratĂ©gie tirant profit d’une combinaison harmonieuse des diffĂ©rentes composantes de la simulation. 

IdĂ©alement, ce stage d’une durĂ©e de 6 mois commencera en Mars 2025 (la pĂ©riode est communiquĂ©e Ă  titre indicatif, et pourra ĂȘtre revue).

Tùches et responsabilités:

Votre tuteur/tutrice vous aidera à identifier vos objectifs professionnels et vous accompagnera dans le développement de vos

compétences. 

Vos principales activités seront les suivantes:

  • Exploration de techniques d’apprentissage avancĂ©es pour prĂ©dire des signaux temporels (sĂ©ries temporelles -ARIMA, LSTM, Sparse Identification of nonlinear dynamics-, modĂšles surrogate -mĂ©thodes de kernel, rĂ©seaux neuronaux profonds-, rĂ©duction de dimension -auto encoders, PCA-)

  • Exploitation des codes internes de simulation physique (vibrations transitoires avec la mĂ©thode des Ă©lĂ©ments finis)

  • Mise en place d’une mĂ©thodologie de quantification des incertitudes de modĂ©lisation

  • Comparaison de diffĂ©rentes mĂ©thodes de rĂ©duction de taille des modĂšles

  • PrĂ©paration d’une stratĂ©gie de simulation hybride efficace exploitant les rĂ©sultats prĂ©cĂ©dents

Ce stage vous permettra notamment de développer les compétences suivantes:

  • CompĂ©tence en modĂ©lisation avancĂ©e (modĂ©lisation physique et par apprentissage)

  • CompĂ©tence concernant la mise en application pratique d'un savoir-faire acadĂ©mique dans le domaine industriel

Votre carte d’embarquement :

Vous préparez actuellement un diplÎme de niveau Bac +5 (ou équivalent) dans le domaine des méthodes numériques ou une discipline apparentée (mathématiques appliquées)  

Vous possédez les compétences suivantes :

  • MĂ©thodes d’apprentissage 

  • MĂ©thodes numĂ©riques (quantification des incertitudes, statistiques, simulation, algĂšbre, traitement du signal)

  • CapacitĂ© d’intĂ©gration dans une Ă©quipe internationale

Compétences linguistiques attendues :

  • Anglais : intermĂ©diaire

  • Français : intermĂ©diaire

Prochaines étapes de notre processus de sélection:

Votre candidature sera analysée par un recruteur/recruteuse dans les prochains jours. Si votre profil correspond aux pré requis, vous serez invité(e) à réaliser un entretien vidéo dont le résultat sera visionné par le recruteur/recruteuse. Si votre candidature est retenue, elle sera alors proposée au manager pour un entretien.

Rejoignez-nous!

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English version:

What if your professional adventure started Airbus !

Are you looking for an internship or for a gap year internship allowing you to validate your diploma this year? We would like to give you the opportunity to work for a world-leading company in its field, focused on digital technology, at the forefront of research and innovation.

We offer an internship: « Machine learning and dynamical systems simulation  (All Gender) » at Airbus SAS in Issy-Les-Moulineaux (France).

You will join the Central R&T department in charge of modelling and applied mathematics.

Your internship will consist in: exploring and developing hybrid approaches, which combine the modelling of dynamical systems with advanced Machine Learning techniques. The simulation of dynamical systems, whether related to the vibrations of a helicopter or to the flow around a wing, remains particularly costly. Such a combination would help reduce the simulation time and give some hope about the possibility to optimise very large structures in the long run.

During this internship, the focus will be put on the analysis of the transient dynamics of a few aeronautical parts and on the way a relevant multi-fidelity modelling strategy can be built up, fed by high-fidelity tools (such as the Finite Element Method) and by learning methods with a degree of accuracy that can be tuned freely based upon the context.

An uncertainty quantification work (to assess the potential and scope of the tools) as well as a model order reduction investigation (to better handle the systems complexity) will help set up a strategy, which benefits in the end from a good balance between the different ingredients of the multi-fidelity simulation.

Ideally, this is a 6-Month internship and it should start in March 2025 (date subject to flexibility). 

This position requires a security clearance or requires to be eligible for clearance by recognized authorities. 


Main tasks and activities:
Your tutor will support you identify your professional objectives and develop your skills. 

You will contribute to the following:

  • Exploration of advanced learning methods to predict time signals (time series forecasting -ARIMA, LSTM, Sparse Identification of nonlinear dynamics-, surrogate modelling -kernel methods, deep neural networks-, dimension reduction -auto encoders, PCA-)

  • Exploitation of internal modelling codes for prediction in physics (focus on transient vibrations with the Finite Element Method)

  • Set up of an Uncertainty Quantification strategy around the models accuracy 

  • Comparison of various methods for model size reduction

  • Preparation of an efficient hybrid simulation strategy that relies on the findings above

This internship will allow you to develop the following skills:

  • Advanced modelling skill (standard methods in physics and more recent ones via learning)

  • Ability to implement and apply academic methods in a practical industrial context

Your Boarding Pass:

You are preparing a diploma level Bac+5 in numerical science (or equivalent, such as applied maths), and you have the following competences:

  • Learning/data methods 

  • Numerical methods (Uncertainty quantification, statistics, simulation, algebra, signal processing)

  • Ability to join an international team

Language skills :

  • French : intermediate

  • English : intermediate

Next steps in our selection process:

Your application will be reviewed by a recruiter. If your profile is matching the key requirements of the job, you will then be invited to perform a short video interview to tell us about your background, motivations and your professional project. The result will be assessed by a recruiter and your application will then be proposed to the manager for further review and interview.

Join us !

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company:

AIRBUS SAS

Employment Type:

Internship

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Experience Level:

Student

Job Family:

Sub-system development

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com.

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Industrial LSTM Machine Learning Mathematics Physics R Research SAS Security Statistics

Perks/benefits: Career development Flex hours Startup environment

Region: Europe
Country: France

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