Imaging Scientist: Subsurface ML & Geophysics

BP; United States; Hybrid; USD 120,000 - 180,000; Full time

Job summary

BP is seeking an Imaging Research Scientist to tackle complex subsurface problems using scientific machine learning, AI, and fundamental physics. The role sits in Imaging R&D within Upstream R&D, collaborating with Geophysics, Petrophysics, and Reservoir Engineering teams on big inverse problems and stochastic algorithms.

You will write code, develop imaging solutions, and communicate uncertainties to business units, handling large datasets and demanding computational tasks in a hybrid

Qualifications

• Advanced degree in scientific field (MS/PhD).
• Demonstrated experience after graduation (3+ years).
• Hands-on coding experience in Python, C, C++, CUDA.
• Experience with inverse problems, optimization theory and statistics.
• Experience with ML/AI and data analytics.

Responsibilities

• Rapidly get up to speed with existing tech and framework.
• Identify opportunities with high business impact.
• Write code and build technical solutions to realize ideas.
• Stay inquisitive, be creative, collaborate across disciplines.
• Work with scientists from multiple subject areas.

Skills

Analytical thinking

Computing

Data analysis

Data management

High-Performance Computing

Numerical analysis

Numerical simulations

Research and development

Statistical machine learning

Statistical physics

Geophysics

Imaging algorithms

Education

MS or PhD in Physics/Mathematics/Computational Sciences/Statistics/Geophysics

Tools

Python

C

C++

CUDA

Job description

BP is seeking an Imaging Research Scientist to tackle complex subsurface problems using scientific machine learning, AI, and fundamental physics. The role sits in Imaging R&D within Upstream R&D, collaborating with Geophysics, Petrophysics, and Reservoir Engineering teams on big inverse problems and stochastic algorithms.

You will write code, develop imaging solutions, and communicate uncertainties to business units, handling large datasets and demanding computational tasks in a hybrid