We are a global technology company, driving energy innovation for a balanced planet.
Together, we create amazing technology that unlocks access to energy for the benefit of all.
At SLB, we recognize that our innovation, creativity, and success stem from our differences. We actively recruit people with a diverse range of backgrounds and cultivate a culture of inclusion that unlocks the benefits of our diversity. We want to ensure that everyone feels a sense of belonging here and we encourage, enable, and empower our people to foster inclusivity, build trust, and demonstrate respect for all across the organization.
Global in outlook, local in practice – and with a united, shared passion for discovering solutions, we hire talented, driven people and support them to succeed, personally and professionally.
The role
Estimating local slopes is important for seismic signal processing. We want to evaluate how a Physics Informed Neural Networks (PINN) could be used for such purpose and how it could help us improving on our existing solutions.
The intern is expected to create a new application by either enhancing existing software or prototyping new one, and to apply such technology to synthetic and real seismic data.
Deliverables
- Enhancing the existing software or prototyping a new solution
- Application of the enhanced software to synthetic data
- Application of the enhanced software to real data
- Writing an internal report and, potentially, submitting a manuscript for a peer reviewed scientific journal
Qualifications and experience
- Ph.D. student in geophysics with experience in the development of deep learning algorithm and Physics Informed Neural Networks in particular.
SLB is an equal opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.