Job category: Subsurface Team
Location: United States – Kansas
We are looking for a full-time staff Geoscientist with interdisciplinary skills in the intersection of mathematics, computer sciences, geosciences and petrophysics.
The candidate will contribute to the fields of geomodeling and petrophysics, uncertainty quantification, mathematical multiscale analysis, predictive and explorative simulations, computational and high-dimensional statistics, data integration, data profiling, heterogeneous data sources, and machine learning.
The candidate will contribute to develop new Geo-Data algorithms, geomodeling and petrophysical workflows, and machine learning algorithms.
Ph.D. in geology, computer science, statistics, or related field.
2+ years of extensive research and /or practical industry experience and proven track record of developing, implementing, debugging, and extending machine learning algorithms and scientific computing.
Experience in workflow automation, automated machine learning and automated geoscience processes and knowledge of GPU programming using CUDA.
Strong background in the log and seismic interpretations.
Strong software engineering and software development skills and object oriented coding expertise in Python.
Experience developing data infrastructure and tools and familiarity with large-scale data processing technologies.
Experience with Real-Time Systems Engineering
Proficiency with the Linux environment
Strong analytical and quantitative skills.
Authorized to work in the US
Post-Doctoral experience in geoscience and machine learning.
Knowledge of modern neural network frameworks.
Experience with cloud computing environments (AWS/Azure/GCE)
Numerical simulation and uncertainty quantifications knowledge and experience.
Relocation available: Negotiable
Travel required: Yes – up to 10%
Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, status as a protected veteran or other characteristics protected by law.