Premium

Fully funded PhD Candidate Position in Digitalization of Supply Chains

Company:ESSCA - School of Management

Location:France / le Havre

Discipline:Digitalization of Supply Chains : Optimization of demand forecasting using Artificial Intelligence Models

Employment Type:Fully funded PhD Candidate Position

Posted:2021-08-18

Fully funded PhD candidate position in Digitalization of supply chains : Optimization of demand forecasting using artificial intelligence models

Essca School of Management / Normandy le Havre University
FRANCE

Offer description

The candidate will simultaneously collaborate with Normandy Le Havre University (NIMEC Lab) and Essca research Lab in FRANCE and work on modeling and forecasting demand by industrial sector. The objective is to develop demand forecasting models in different industries, with different forecast horizons and time scales. These models will be integrated into the forecasting system currently in service. The project is carried out in close collaboration with Colibri, a cloud supply chain Planning solution for many sectors such as industry, trade and distribution, retail…. Machine learning techniques will be used and integrated into Colibri's forecasting tool.

The ideal candidate will have:

  • A solid background in supply chain/ operations management and computer science. Special areas of interest include demand forecasting, machine learning, mathematical optimization and modeling.
  • He or she should have completed, or about to complete, an MSc in the above areas.
  • A good understanding of machine learning methods and algorithms.
  • good programming skills in Python or ability to develop fast competencies in programming with Python.
  • Excellent command of English.
  • Team work capacity.

Scientific procedure

  1. Writing of a state of the art on forecasting demand by business sector and its impact on the performance of the Supply Chain and consideration of the product life cycle.
  2. Production of forecasting models by sector of activity and comparisons with classical statistical models.
  3. Development of decision support models in the event of a disruption in the supply chain.
  4. Scientific publications Alongside the decision-making tools, which will be developed for the company, using real data, this thesis is a thesis by articles which makes it possible to integrate articles published or ready to be published in peer-reviewed journals recognized in the disciplinary field of the thesis based on the proposed scientific approaches (in general at least three articles).

The application must include:

  • A research proposal (5 to 10 pages)
  • A detailed curriculum vitae (academic background and research experience)
  • A letter of motivation
  • One to three letters of recommendation

Please send your applications to atour.taghipour@univ-lehavre.fr and Chaaben.KOUKI@essca.fr

Contact Person:If you wish to apply for this position, please specify that you saw it on AKADEUS.

Previously Viewed: