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Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 22, 2026. SLB scores B on the Alion truth index.

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SLB

Headquartered in Houston, Texas, SLB (formerly known as Schlumberger) is a global energy technology company specializing in innovative solutions for the oil and gas industry. The enterprise provides a comprehensive range of services and digital technologies, spanning well construction, reservoir performance, and production optimization. Operating in over 120 countries, SLB also drives clean energy initiatives, supporting decarbonization, carbon capture, and new energy systems worldwide.
Backed by Aramco Ventures

Job Title:

Data Scientist Intern (12 months) - Starting Summer 2027

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 https://www.slb.com/who-we-are

Location:

Cambridge, UK

SLB Cambridge Research (SCR) is part of SLB’s global network of research and engineering centres. SCR is a dynamic, multidisciplinary environment with state-of-the-art research and computing facilities. We work on applied research projects in the physical sciences to meet the current and future challenges of the industry.

Description & Scope:

Real-world systems from industrial processes to environmental monitoring are never fully observed. Sensors fail, data arrives late, and no single measurement tells the whole story. This project explores how to intelligently combine heterogeneous, incomplete data streams while rigorously quantifying what we do not know. Using probabilistic machine learning, Bayesian inference, and uncertainty-aware neural architectures, you will build models that are honest about their own confidence producing not just predictions, but trustworthy estimates with calibrated uncertainty bounds. The result: smarter, more reliable AI for complex systems where measurement is imperfect and decisions are high-stakes.

Responsibilities:

Develop methods to fuse incomplete sensor data and handle uncertainty. Build ML models that deliver both predictions and confidence levels. Gain hands-on experience with data fusion, uncertainty quantification, and applied AI.

Requirements :

  • Studying Bachelors in Bachelors in Data Science, ML, AI or a related discipline

  • Python

  • Data analysis

  • Machine learning

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.

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