Machine Learning / AI / Hybrid Models Intern – Physics-informed models for energy applications (6 months)

December 11, 2021

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Job Overview

  • Date Posted
    December 11, 2021
  • Expiration date
  • Gender
  • Field
  • Qualification
    M. Sc., Dr.
  • Section

Job Description



Clamart, France

About Schlumberger:

We are Schlumberger, the leading provider of technology and services to the energy industry. Throughout much of the oil and gas lifecycle in over 120 countries; we design, develop, and deliver technology and services that transforms how work is done.

We define the boundaries of the industry by unleashing our talented people’s energy. We’re looking for innovators to join our diverse community of colleagues and develop new solutions and push the limits of what’s possible. If you share our passion for discovery and want to find out what you could really do, then here is the place to do it.

Job Summary:

Recently, there has been a growing interest in integrating traditional physics-based models with machine learning (ML) techniques. Building a physics-informed or “hybrid” model can have different motivations and end goals. The overall vision of hybrid models is to introduce scientific consistency as an essential element for learning generalized models. In the Energy domain, domain experts seek to interpret data from drilling. In some cases, the experts have the physical models used for this task. However, these models remain approximations of complex cases and are not able to accurately represent the underlying process. Moreover, they can contain many parameters whose values must be estimated with limited data, degrading their performance further.

The objective of this internship is therefore to analyze state-of-the-art methods for different Oil & Gas applications. The main approach of the work is to select relevant features based on physics, before injecting physics directly into the core of algorithm.

The intern will have the opportunity to do a high-level theoretical and applied research in this field, contribute to new product developments and work with project experts and data scientists from the AI Lab located on Clamart Campus.

The intern will be in charge of defining the best strategy and methodology to provide a new answer product based on data science technologies (statistics and machine learning algorithms). The intern will have the opportunity to use available experimental equipment and numerical tools (large possibilities within Schlumberger with research and engineering centers).


  • Master’s degree – 2nd year or final year of Engineering School



  • applied mathematics
  • probability & statistics
  • deep learning
  • time series
  • Bayesian statistics
  • manifold learning
  • embedded software
  • physics/electronics (in general)

Cloud computing services:

  • Google Cloud Platform


  • Python
  • PyTorch or
  • Keras/Tensorflow

Schlumberger 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.