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ExxonMobil

Produces oil, gas, fuels and chemical materials

Computational Scientist

Applied Machine LearningUpdated on Nov 14
Full-timeSpring, TX, USAIn-person

About the Job

Requirements

  • A PhD from a recognized university in Engineering, Applied Mathematics, Geoscience, Computational Science, or a closely related field is required.
  • Experience developing, applying, and analyzing physics-based models and developing related algorithms is required.
  • A strong background in multiscale and/or multiphysics mathematical modeling, scientific computing, and numerical analysis is required.
  • Hands-on experience with deep learning, including familiarity with autoencoder, transformer, diffusion model, and GAN architectures and their application to industrial, engineering, or scientific problems, is required.
  • Experience in surrogate modeling approaches, including deep learning, machine learning, physics-informed machine learning, reduced-order modeling, or multi-fidelity methods, to reduce computational cost in decision-making processes such as optimization, inverse problems, and data assimilation while maintaining fit-for-purpose accuracy is required.
  • Experience formulating and solving convex and PDE-constrained optimization problems is required.
  • Strong proficiency in Python or C++/C# programming and scripting languages is required.
  • Proficiency in ML frameworks such as PyTorch, TensorFlow, and scikit-learn is required.
  • Experience with software engineering best practices, including software testing, agile development, version control, and DevOps, is required.
  • Strong communication skills and the ability to work effectively in interdisciplinary teams to translate complex computational models into actionable insights are required.

Responsibilities

  • Collaborate across global, cross-disciplinary teams and with third parties, including academia and industry, to assess and accelerate the development and deployment of computational science technology.
  • Frame computational challenges from business needs and develop solutions that balance accuracy and runtime, merge physics and data while incorporating uncertainty, and use novel approaches to constrain predictive models with field data.

Desired Qualifications

  • Experience with Databricks or Spark is a plus.
  • Experience working in Linux and high-performance computing environments is desirable but not required.
  • Prior experience in the upstream oil and gas industry is an advantage.

About the Company

ExxonMobil

Produces oil, gas, fuels and chemical materials

ExxonMobil produces oil and natural gas and manufactures fuels, lubricants, and chemicals for transport operators, industrial customers, and consumers around the world. Its businesses span resource exploration and production, refineries that turn crude oil into fuels, and plants that make plastics and other chemical materials. The company sells products through wholesale supply agreements and the Exxon, Esso, and Mobil brands, including motor oils for vehicles and machinery. It also sells services that capture, transport, and store industrial carbon dioxide underground. The merged company formed in 1999 from Exxon and Mobil, with roots in earlier oil businesses, and is headquartered in Spring, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Spring, TX
Founded
1999

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