Job Summary
ExxonMobil is seeking a highly skilled and motivated Computational Scientist to join our team at our state-of-the-art campus in Spring, Texas. In this role, you will develop and analyze both physics-based and data-driven computational models to solve complex challenges in the oil and gas industry. You will work across global, cross-disciplinary teams to accelerate the development and deployment of computational science technologies that advance modern living and a net-zero future.
Postdoctoral research as a Computational Scientist in Spring, Exxon Mobil, USA
Key Job Details
| Category | Details |
|---|---|
| Designation | Computational Scientist |
| Company | ExxonMobil |
| Location | Spring, TX, US, 77389 (Houston Area) |
| Research Area | Mathematical Modeling, Scientific Computing, Deep Learning, and Surrogate Modeling |
| Employment Type | Full-Time |
What You Will Do (Job Description)
- Collaborative Development: Work across global, cross-disciplinary teams and alongside third parties (academia, industry) to assess and accelerate the pace of computational science technology development and deployment.
- Problem Solving: Frame computational challenges from business needs and design solutions that strike an optimal balance between accuracy and runtime.
- Hybrid Modeling: Merge physics and data-driven approaches while incorporating uncertainty, and develop novel ways to constrain predictive models using field data.
Eligibility & Qualifications
Required Education
- Ph.D. from a recognized university in Engineering, Applied Mathematics, Geoscience, Computational Science, or a closely related field.
Technical Skills & Experience
- Modeling & Algorithms: Strong background in multiscale and/or multiphysics mathematical modeling, scientific computing, numerical analysis, and developing related algorithms.
- Deep Learning: Hands-on experience with deep learning architectures (e.g., autoencoders, transformers, diffusion models, GANs) applied to industrial, engineering, or scientific problems.
- Surrogate Modeling: Experience with surrogate modeling approaches (e.g., machine learning, physics-informed machine learning, reduced-order modeling, multi-fidelity methods) to reduce computational costs in decision-making processes like optimization and data assimilation.
- Optimization: Experience formulating and solving convex and PDE-constrained optimization problems.
- Programming & Frameworks: Strong proficiency in Python or C++/C#, and ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
Preferred (Nice-to-Have)
- Experience with Databricks/Spark.
- Experience working in Linux and High-Performance Computing (HPC) environments.
- Prior experience in the upstream oil and gas industry.
- Familiarity with software engineering best practices (testing, agile development, version control, DevOps).
Benefits & Perks
- Pension Plan: Automatic enrollment at no cost, providing a monthly annuity in retirement.
- Savings Plan: Company match of up to 7% if you contribute at least 6% of your pay.
- Workplace Flexibility: Programs like “Flex your Day” for ad-hoc flexibility, alongside longer-term leave programs.
- Health & Wellness: Comprehensive medical, dental, and vision plans, plus confidential mental health counseling via the Employee Health Advisory Program.
How to Apply
To apply, submit your application directly through the official ExxonMobil careers portal:
Last Date to Apply
- Application Deadline: Open Now
Note: ExxonMobil typically keeps high-priority technical roles open until filled. However, a system upgrade is scheduled from mid-March through early April, which may cause temporary application processing delays. Early submission is highly recommended.
