Internship - AI Engineer - Uncertainty estimation and active learning (6 mo

<b> Job title: </b><br> <br> Internship - AI Engineer - Uncertainty estimation and active learning (6 months)<br><br><b> About Us: </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> Location: </b> Clamart, France<br> <br> Come and Join SLB's AI Lab in Paris. We are currently offering internship to bright minds specialized in Data Science and Artificial Intelligence. Discover a multinational company. We have brought a little bit of the Silicon Valley in Paris. Experience working within a team of young and fun passionate Data Scientists, tackling real business challenges, in tandem with business experts who are sitting at your desk.<br> <br> The Artificial Intelligence & Machine Learning Data Scientist helps develop software and processes that can be used for robotics, artificial intelligence programs and application. In close collaboration with the business and metiers, the data scientist offers mathematical and statistical models from the collected data to augment, improve or speed up human decisions within the Energy sector. With SLB you will be given the opportunity to apply your expertise and deploy deep learning solutions at scale on real-world problems, supporting many areas of SLB's business. SLB is the first Energy service company to move its processes and workflows in the cloud. This gives the Embedded AI Lab the perfect opportunities to leverage these innovative technologies and resources. As part of the Embedded AI Lab you will be able to test, experiment and research with the bleeding edge environment with Petabits and Petabits of data. You will be in charge of applying research and delivery of Proof of Concepts solutions, responding to a clear and specific business needs.<br><br><b> Description: </b><br> <br> Two of the biggest issues preventing the widespread use of machine learning in the Energy industry is the need for expert labelled data, and the lack of confidence in the trained models. The issue with expert labelled data is that the experts generally only have a very limited amount of time available for such labelling. This means that any project must limit itself to the very minimum number of labels necessary. The issue with confidence in the trained models on the other hand, is the lack of knowledge of when the model can be trusted or not. Given data similar to the training data the model might indeed perform very well, while it can fail catastrophically when the data becomes sufficiently different from the training data. Is there a way for the model itself to predict such failures, and tell us when and when not it should be trusted?<br> <br> These two seemingly disjointed topics are brought together in the field of