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- Tasks: Join our team to develop innovative AI solutions for energy challenges.
- Company: SLB, a global leader in energy technology and innovation.
- Benefits: Gain hands-on experience, mentorship, and potential publication opportunities.
- Why this job: Make a real impact on energy sustainability while advancing your skills.
- Qualifications: Masters in relevant fields and proficiency in Python and C++.
- Other info: Inclusive workplace with opportunities for growth and adaptation.
Job Title:
AI Engineer Intern (3 or 6 months) – Starting Summer 2026
Project Title: Application of a cell-based machine learning model as a non-linear solver pre-conditioner
About SLB:
We are a global technology company, driving energy innovation for a balanced planet.
At SLB we create amazing technology that unlocks access to energy for the benefit of all. That is our purpose. As innovators, that has been our mission for 100 years. We are facing the world\’s greatest balancing act- how to simultaneously reduce emissions and meet the world\’s growing energy demands. We\’re working on that answer. Every day, a step closer.
Our collective future depends on decarbonizing the fossil fuel industry, while innovating a new energy landscape. It\’s what drives us. Ensuring progress for people and the planet, on the journey to net zero and beyond. For a balanced planet.
Our purpose: Together, we create amazing technology that unlocks access to energy for the benefit of all. You can find out more about us on
Location:
Abingdon, Oxfordshire
Description & Scope:
In reservoir simulation, a system of non-linear equations is discretized and solved implicitly using the Newton-Raphson method. To enhance solver performance and convergence, various strategies are employed, including inexact Newton methods, preconditioning techniques, multiscale solvers, and others.
This internship explores the integration of a Neural Network (NN) single-cell method as a preconditioner for the non-linear system. The approach involves collecting simulation runtime data for each grid cell and feeding it into a pre-trained neural network to generate improved initial guesses prior to invoking the non-linear solver.
This technique is inspired by the methodology presented in \”Learning to Solve Parameterized Single-Cell Problems Offline to Expedite Reservoir Simulation\” by Abdul-Akeem Olawoyin and Rami Younis (SPE MS, 2023).
Responsibilities
The intern will work closely with the Intersect innovation team to implement and test the pre-conditioner inside Intersect code. By the end of the internship the following technical deliverables are expected:
- Coupling pre-trained neural-network models with an existent commercial simulator to create a pre-conditioner for the non-linear solvers
- Testing different neural-network architectures to identify how to best solve this problem
- Propose an automatic method to export simulation data in a structured format, to be used as training data for the pre-conditioner
- This an innovation work, with an opportunity to publish it in a research journal.
Qualifications:
- Studying a Masters in Software development, Artificial Intelligence, Neural Networks, Machine Learning, Numerical methods or a related discipline
Python and C++ coding languages, neural-network model and training, numerical methods for solving ODEs and PDEs.
SLB is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.
The recruiting process and the position can be adapted to fit most disabilities, please do not hesitate to mention this when applying.
AI Engineer Intern (3 or 6 months)
AI Engineer Intern employer: SLB
Contact Detail:
SLB Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer Intern
✨Tip Number 1
Network like a pro! Reach out to current or former interns at SLB on LinkedIn. Ask them about their experiences and any tips they might have for landing the role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for technical interviews by brushing up on your Python and C++ skills. Work on some machine learning projects or coding challenges that relate to neural networks. Show us what you can do!
✨Tip Number 3
Don’t forget to showcase your passion for energy innovation! When you get the chance, talk about how your skills can contribute to decarbonising the fossil fuel industry. We love candidates who align with our mission.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows us you’re serious about joining the team. Let’s make this happen together!
We think you need these skills to ace AI Engineer Intern
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Engineer Intern role. Highlight your experience with Python, C++, and any relevant projects involving neural networks or machine learning. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for energy innovation and how you can contribute to our team. Don’t forget to mention any specific projects or experiences that relate to the internship.
Showcase Your Projects: If you've worked on any cool projects related to numerical methods or neural networks, make sure to include them in your application. We love seeing practical examples of your work and how you approach problem-solving!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our innovative team!
How to prepare for a job interview at SLB
✨Know Your Stuff
Make sure you brush up on your knowledge of neural networks and numerical methods. Familiarise yourself with the Newton-Raphson method and how it applies to reservoir simulation. Being able to discuss these concepts confidently will show that you're genuinely interested in the role.
✨Showcase Your Coding Skills
Since Python and C++ are key for this internship, be prepared to talk about your coding experience. Bring examples of projects you've worked on, especially those involving machine learning or numerical methods. If possible, demonstrate your problem-solving approach during the interview.
✨Ask Insightful Questions
Prepare some thoughtful questions about the team and the projects you'll be working on. This shows your enthusiasm and helps you understand how you can contribute. For instance, ask about the specific challenges they face with integrating neural networks into their existing systems.
✨Be Ready to Discuss Innovation
This internship is all about innovation, so think about how you can bring fresh ideas to the table. Be ready to discuss any innovative approaches you've taken in past projects or how you would tackle the integration of a neural network as a pre-conditioner. Show them your creative side!
