PhD position in Lille (France): Bayesian models for forecasting in the supply chain

PhD position in Lille (France): Bayesian models for forecasting in the supply chain

Overview

Bayesian models for forecasting in the supply chain. The objective of the thesis is to predict the evolution of the outputs in the supply chain, i.e. quantities in locations of storage or sales. The research work is divided into two parts: (1) mathematical modeling of the supply chain, and (2) inference methods for prediction. First, we model the problem in a probabilistic and generic way, taking into account all possible interactions between the variables of interest. In the second part, we develop Bayesian methods for probabilistic prediction at all stages of the chain. We propose novel efficient and accurate algorithms, including but not only sequential learning, to avoid the need to reprocess all past data every time new data is available.

Where and When

One fully funded PhD position is available in Lille from September/October 2018. The thesis will take place jointly at the engineering school IMT Lille Douai and at a fast-growing company focused on machine learning and data science. Earlier start date can be considered. Lille is a vibrant, young and dynamic city. Lille lies in the heart of the triangle that links three of Europe’s main metropoles: London (80 min), Paris (60 min), and Brussels (35 min).

Candidate profile

We are looking for a motivated and talented student with:

• background in machine learning, signal processing, statistics or applied mathematics
• strong mathematical skills
• experience in programming, preferably in Matlab and/or Python

Contact

If you have any question and/or want to apply, please contact: