Project Title: Proof-carrying Neural Network Controllers.
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 decarbonising 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.
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.
This internship will explore proof-carrying neural network controllers. Neural-network-based decision and control policies are deployed together with machine-checkable formal proofs that certify critical safety and mission properties. The project aims to combine Vehicle for specifying and proving high-level requirements over neural networks, Rocq for constructing and checking machine-verified correctness arguments, and Marabou for automated verification of network behaviour under bounded operating conditions.
The intern will investigate how mission guarantees can be generated, composed, and attached to trained controllers. The longer-term vision is to establish a practical assurance pipeline where neural controllers can be continuously updated while retaining independently checkable proofs, enabling greater trust, auditability, and certification readiness for autonomous systems operating in real-world environments.
Interns will be mentored and responsible for developing the direction of the project in a supported-learning environment. They will experience the development of prototype solutions and interact with scientists, domain experts and end-users to enable the testing of the prototypes.
The intern will:
SLB is an equal employment opportunity employer. Qualified applicants are considered without regard to race, colour, 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.
