Artificial Intelligence Intern - Neuro-Symbolic AI for energy applications

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Job description

Job title:

Artificial Intelligence Intern - Neuro-Symbolic AI for energy applications (6 months)

Location:

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:

Neuro-Symbolic AI, the combination of two existing approaches to building an AI system, allows us to combine both learning and logic. Symbolic AI refers to the expert system, in which the real world is understood and described by symbolic representations and the rules between them. It has been widely used in industry. The "neuro" section refers to deep neural networks, which has driven many AI breakthroughs over the past decade. Unlike symbolic AI, neural networks are data-driven rather than rule-based. In combination, neural networks automatically segmenting the world into symbols will make symbolic AI feasible for complicated tasks.

Meanwhile, symbolic AI algorithms will help integrate conventional reasoning and domain knowledge into deep learning. The results could lead to significant advances in AI systems that enable us to tackle many complex tasks. The combination provide a strong capability for interpretability, which is very important in many industrial tasks while requiring far less data for training.

Essential Responsibilities and Duties:

The purpose of this internship is to analyze the state-of-the-art neuro-symbolic AI methods that could be adopted for different Oil & Gas applications, and develop techno bricks for some detail applications such as quality control check, energy production control, etc.

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. The intern will have the opportunity to use available experimental equipment and numerical tools (large possibilities within Schlumberger with research and engineering centers).

Qualification:

• Master's degree - 2nd year or final year of Engineering School

Competencies:

• Skills: Time series, Applied mathematics, probability & statistics, deep learning
• Programming language: Python, PyTorch or Keras/Tensorflow

References:

Mao, Jiayuan, et al. "The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision." arXiv preprint arXiv:1904.12584 (2019).

De Raedt, Luc, et al. "From statistical relational to neuro-symbolic artificial intelligence." arXiv preprint arXiv:2003.08316 (2020).

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.