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Mantle8 is a deep-tech exploration company focused on unlocking natural hydrogen as a clean energy resource. This role combines R&D and production work in seismic imaging and full waveform inversion (FWI).
R&D Responsibilities:
- Design, develop, and adapt FWI workflows for passive seismic data, from raw data to velocity model
- Build and optimize forward-modeling and adjoint-based inversion components: gradient, misfit functions, regularization, and uncertainty quantification
- Benchmark on synthetic models, then apply to Mantle8 field datasets
- Assess and extend open-source codes (SPECFEM, Salvus, Devito, SeisFlows, ObsPy) with attention to licensing
- Run and optimize inversions on HPC and cloud infrastructure
Production Responsibilities:
- Process dense nodal-array datasets (Stryde, SmartSolo): pre-processing, Green's-function retrieval, source characterization
- Apply established methods—ambient-noise tomography, traveltime tomography—to deliver models within project timelines
- Share clear results with geologists and geochemists; integrate with other geophysical data
- Contribute to acquisition design (array geometry, sensor selection)
- Document methods, code, and write technical reports
First Milestones:
- Months 1–3: take ownership of data and tools, choose the code base, run first synthetic tests
- By month 6: deliver first FWI results on Mantle8 field data
The team is international (21 people, 9 nationalities as of March 2026) and based in the French Alps. You'll have access to proprietary datasets, freedom to publish and present at conferences, an interdisciplinary geoscience team, and modern computing resources. Health insurance is fully covered for employees, plus meal vouchers and CESU benefits.
Requirements:
- PhD in seismology, geophysics, applied mathematics, or related field with thesis focused on full waveform inversion
- Early career: recent PhD graduate, up to 5 years of experience post-PhD
- Hands-on development of FWI code: must have written, tested, and benchmarked significant parts of an inversion workflow (not just used commercial software as a black box)
- Complete understanding of the FWI protocol from data to model, with in-depth knowledge of each component
- Solid background in seismology and wave propagation
- Strong scientific programming (Python and/or C/C++, Fortran, Julia), numerical methods, and Git
- Experience with HPC and parallel computing
Desirable:
- Passive seismology: ambient-noise interferometry, teleseismic or microseismic data
- Ambient-noise or traveltime tomography in applied settings
- Machine learning for seismic data
- Joint inversion or exploration geophysics
Personal Qualities:
- Adaptability when working with complex, noisy data
- Autonomy, rigour, and ability to deliver on deadlines
- Clear communication within multidisciplinary teams
- Working proficiency in English; French is a plus
- Non-linear career paths welcome; expertise matters most
Application Note: Please include a short description of the FWI code you have developed (scope, language, open-source or not). A link to a repository is welcome.
