Stage - R&d - Hybridation Ia & Ro Pour L'optimisation Des Capacités Dans Un Processus S&op H/f

Air Liquide

Les Loges, France
Hybrid
Machine learning and operational research
Python programming (pyomo, gurobipy)
Stochastic optimization methods
You will contribute to shaping the supply chain of the future by focusing on the implementation of hybrid machine learning and operational research methods

Job Summary

  • You will contribute to shaping the supply chain of the future by focusing on the implementation of hybrid machine learning and operational research methods.
  • The central problem of this internship is to develop a decision support tool for the optimal sizing of the gas cylinder fleet, a complex decision due to the uncertainty of future demand and empty cylinder returns.
  • Air Liquide is committed to building a diverse and inclusive workplace that embraces the diversity of its employees, customers, patients, community stakeholders and cultures across the world.

Matching Summary

You will contribute to shaping the supply chain of the future by focusing on the implementation of hybrid machine learning and operational research methods.

Skills & Requirements

Must-have

  • Machine learning and operational research
  • Python programming (Pyomo, Gurobipy)
  • Stochastic optimization methods
  • Time series forecasting
  • Industrial data analysis

Nice-to-have

  • Scientific curiosity and creativity
  • Teamwork and communication skills
  • Applying theoretical methods to industry

Key Requirements

  • 3rd year engineering school or Master 2
  • Operational Research background
  • Machine Learning background
  • Python programming skills
  • Interest in industrial applications

Work Rights

Not specified

Tailored Resume

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