Internship - AI Engineer – Comparative Study of Balancing Techniques for Image Classification with Imbalanced Datasets (6 months)

Key Skills

Aartificial intelligence, Algorithms, Augmented Reality (AR), dense 3D reconstruction, Feature Extraction, Keras software library, Large scale deployment, Mathematical optimization, Mathematics, Natural Language Processing (NLP), Python Programming, PyTorch, Regression Analysis, Statistical modeling, Statistics, TensorFlow, Terabyte scale datasets

Job Description

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’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.

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: Clamart, France

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.

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 métiers, 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.

Description:

Imbalanced datasets with long-tailed distributions are widely spread in real-world scenarios including datasets acquired with remote sensing technologies in various geological settings. When used in classification tasks they cause a bias in a decision boundary for machine learning and deep learning-based solutions, resulting in a smaller feature space for rare classes. In this internship project, we aim to conduct a comparative study of balancing techniques to address this challenge.

Computer vision datasets with ultrasonic, electromagnetic and microscope borehole images have been already collected internally and from publicly available sources and will be available within the scope of this internship. This will enable us to explore the application of different balancing techniques including off-line data manipulation methods (over-sampling / under-sampling, stratified splits), cost function weighting and especially recently proposed plug-and-play approaches (on-line rare class samples generation, on-line pseudo-labels generation, etc).

The main goal of this internship is to build a cumulative foundation of techniques devoted to enable vision-based deep learning models to efficiently discover structure within datasets with imbalanced data distribution and generalize well to infrequent classes. This has a wide application benefiting well integrity and well construction projects across SLB.

Required skills:

General: applied mathematics, probability & statistics, image processing, image classification and segmentation, deep learning models like CNNs, Siamese Networks, Autoencoders

Programming: Python, PyTorch or Keras/Tensorflow

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.