Post-doctoral research visit f - m acceleration of full waveform inversion for seismic inversion applications h/f

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'eorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie. Post-Doctoral Research Visit F/M Acceleration of Full Waveform Inversion for Seismic Inversion Applications
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD

Niveau de diplôme exigé : Thèse ou équivalent

Fonction : Post-Doctorant

Niveau d'expérience souhaité : Jusqu'à 3 ans

Contexte et atouts du poste

The Makutu project team specializes in large-scale simulations applied to the reconstruction of complex media, used to gain a better understanding of the internal dynamics of environments that are difficult or even impossible to probe. To this end, it develops advanced numerical methods that are integrated into open-source platforms deployed on state-of-the-art HPC environments.

Full-Waveform Inversion (FWI) is a powerful imaging technique that aims to recover physical parameters of a medium by minimizing the misfit between observed and simulated wavefields. It plays a central role inparticular in subsurface exploration(e.g., geophysics).

In thefrequency domain, FWI involves solving large-scale wave equations at multiple frequencies. This leads to the repeated inversion of very large, often ill-conditioned, linear systems - beyond the capabilities of standard direct solvers. Whileiterative solversoffer an alternative, they raise significant algorithmic challenges, particularly in themultiple right-hand sidessetting, which is crucial for inversion involving multiple sources. Additional strategies also have to be investigated to reduce the computational cost of wave modeling, such as reduced-order models or learning-based techniques. In both cases, the compromise between accuracy of the solutions and the computational cost has to be carefully handled.

This postdoctoral position offers a unique opportunity to combine advanced numerical methods with machine learning to accelerate and enhance FWI. The successful candidate will gain expertise in high-performance computing while working within a dynamic team involved in flagship projects such as INCORWAVE (ERC) and Exa-MA (PEPR Numpex). Strong international collaborations will provide an excellent environment for developing cutting-edge research.

Mission confiée

The successful candidate will contribute to the development and evaluation ofacceleration strategies for frequency-domain FWI, by combining numerical methods, model reduction techniques, and learning-based approaches. Potential research directions include (but are not restricted to):
- Leveragingreduced-order models(e.g., via Proper Orthogonal Decomposition, SVD, or projection-based techniques) to accelerate the direct solution phase.
- Applyingmachine learning techniques(e.g., neural networks, statistical models) tointerpolate or predict frequency responses, enabling significant savings in frequency sampling.
- Exploitingmatrix structures(e.g., block patterns, low-rank properties) in discretized wave equations.
- Designing efficientpreconditionersfor iterative solvers (e.g., Krylov, block Krylov methods) or any DDM inspired method
- Developing scalablemulti-right-hand-side solversadapted to inversion workflows.
- Exploringhybrid approachesthat combine direct solvers (possibly partially factorized) with iterative schemes.

These developments will be validated on representative test cases inseismic imagingandhelioseismic inverse problems, in collaboration with domain specialists. The computational developments and new methodologies will be implemented in the open-source software hawen ().

Principales activités

The recruited postdoctoral researcher will be expected to take an active role in the team's scientific and collaborative activities, with missions including:

- Scientific monitoring & knowledge sharing: conducting regular technology watch and maintaining an updated bibliography, shared with the team.
- Collaboration & teamwork: engaging with team members through dedicated working groups closely related to the postdoctoral topic.
- Software development & documentation: systematically documenting all software contributions to ensure reusability and accessibility for both the team and external users.
- Research dissemination: writing research reports, presenting results at international conferences, and publishing in peer-reviewed journals.
- User engagement & training: providing training for key users of the service and contributing to the animation of an active user community.
- Partnership & outreach: presenting project progress to partners, including stakeholders and funding bodies.
- Additional contributions: supporting other scientific and technical activities relevant to the project.

Compétences

- Software development: solid programming skills, with good practice in HPC environments particularly valued.
- Collaboration & communication: strong interpersonal skills with a focus on teamwork; ability to present results to both scientific and non-scientific audiences (including funding bodies).
- Languages: fluency in English (written and spoken).
- Other qualities: autonomy, scientific curiosity, initiative, and a strong commitment to collaborative research.

Avantages

- Subsidized meals
- Partial reimbursement of public transport costs
- Possibility of teleworking 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

Rémunération

2788€ per month before taxs