Ph.D research project Califrais x LPSM - Machine learning based hybrid strategies for combinatorial optimization
Context
Rungis Market is the largest fresh produce market in the world, in particular, it supplies 63% of the food consumed in Ile-de-France. The company Califrais is its official digital and logistics operator through the platform rungismarket.com. With the aim of digitalizing and decarbonizing the food supply chain, Califrais develops logistics solutions based on algorithms at the crossroads of machine learning, statistics, and optimization.
Califrais has strong connections with public research and works with academic partners such as the Laboratoire de Probabilités, Statistique et Modélisation (LPSM), Sorbonne Université and the CNRS.
This privileged context has led to numerous publications in leading conferences of machine learning, such as ICML and NeurIPS.
They are offering this Ph.D. position as part of a collaboration between Califrais and the LPSM. Its aim is to study recent tools at the intersection of machine learning and combinatorial optimization that allows to jointly “learn and optimize”. It is funded by the French Agency for Ecological Transition (ADEME) under the call “Logistique 4.0” won by Califrais and Sorbonne Université.
Practical conditions
This Ph.D. is part of a collaboration between Califrais and the LPSM at Sorbonne Universit´e, funded by a grant from ADEME.
- Location: the internship will take place in both locations (Paris 75005 and Paris 75010)
- Starting date: Autumn 2025
- Duration: 3 years
- Profile: M2 research in applied mathematics or third year of engineering school
- Grant: 2 200 e/month before tax
The supervising team will consist of:
- Adeline Fermanian, Califrais
- Maxime Sangnier, Sorbonne Université
Application
The application file containing:
- a resume;
- a cover letter;
- a transcript of grades (Bachelor’s and Master’s degrees)
- should be sent by mail to [email protected] and [email protected].