Geophysics ML Intern: FWI & Elastic Seismic Imaging

Viridien; Massy; Presencial; EUR 13.000 - 18.000; A tiempo parcial

Ventajas ofrecidas por este puesto de trabajo

International culture

Restaurant access

Transport subsidy

Mobility incentive

Gym access

Employee assistance program

Descripción de la vacante

Viridien is seeking a final-year Master student to work on advanced Earth imaging challenges as a six-month internship in Massy, France. You will apply analytical and problem-solving skills to develop, test, and refine methods for reservoir-oriented Full-Waveform Inversion (FWI) using neural networks and petrophysical information.

You will collaborate with our subsurface imaging R&D team, extend neural network mappings to elastic parameters, and contribute to cutting-edge geophysics research in

Formación

• Final-year Master student in Mathematics, Physics, Computer science, Artificial intelligence, Data science, or Natural Sciences with a Mathematics/Physics specialization
• Solid understanding of machine learning algorithms and neural network architecture
• Excellent coding skills with Python, C/C++, CUDA, FORTRAN

Responsabilidades

• Investigate the potential of using neural networks to incorporate petrophysical information for guiding full-waveform inversion (FWI) from both methodology and development perspectives
• Develop a neural network model to map petrophysical parameters (porosity, lithology, saturation) to elastic parameters (Vp, Vs, density, …)
• Integrate the neural network mapping into the FWI framework, allowing the inversion to be guided by petrophysical information

Conocimientos

Machine Learning

Geophysics basics

Python

C/C++

CUDA

FORTRAN

Analytical problem solving

Fluent English

Educación

Master’s degree – final-year

Herramientas

Python

C/C++

CUDA

FORTRAN

Descripción del empleo

Viridien is seeking a final-year Master student to work on advanced Earth imaging challenges as a six-month internship in Massy, France. You will apply analytical and problem-solving skills to develop, test, and refine methods for reservoir-oriented Full-Waveform Inversion (FWI) using neural networks and petrophysical information.

You will collaborate with our subsurface imaging R&D team, extend neural network mappings to elastic parameters, and contribute to cutting-edge geophysics research in