Internship - Software Engineer + AI - Optical instrumentation prognostic he

<b>Internship - Software Engineer with knowledge in AI - S189</b><br> <br> <b>Optical instrumentation prognostic health management</b><br><br><b> About SLB </b><br><br>We are a global technology company, driving energy innovation for a balanced planet.<br> <br> At SLB we create amazing technology that unlocks access to energy for the benefit of all. That is our purpose. As innovators, that's 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.<br> <br> 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.<br><br><b> Our Purpose </b><br><br>Together, we create amazing technology that unlocks access to energy for the benefit of all.<br> You can find out more about us on company website<br><br><b> Job title </b><br><br>Internship - Optical instrumentation prognostic health management (5-6 months)<br><br><b> Location </b><br><br>Clamart, France<br><br><b> Description </b><br> <br> Distributed Sensing Interrogators have an internal optical switch. Currently there are no built-in feature in any interrogator which flags the failure of the switch. In case of failure happens, it could be diagnosed by expert by looking at the data recorded by interrogator. In practice the failures are diagnosed only after several months after it actually occurred.<br> <br> After SLB decided to outsource the manufacturing of interrogators, it became even more important to diagnose the failure straight away after it appears, in order to ensure proper product quality assessment. <br> <br> The project scope could be also extended to other types of Fiber Optic system failures, such as fiber darkening detection, fiber break detection, detection of bad connectors..<br><br><b> Possible Responsibilities and Duties </b><br> <br> To develop automatic failure detection algorithm based on AI model which analyses the data received by interrogator. This algorithm could be integrated into existing control software. The expertise on Distributed Sensing hardware could be provided by Fiber Optic Hardware team. The potential educational background of intern could be - software developer with knowledge (or interest) of AI-based equipment failure detection algorithms.<br><br><b> Target Disciplines and Special Skills </b><br> <ul> <li> Penultimate or final year of MSc in Computer Science or similar Engineering degree</li> <li> Full stack software development</li> <li> Artificial Intelligence</li> <li> Machine Learning</li> </ul> <br><br>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.