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PhD in material science (M/F)

This offer is available in the following languages:
Français - Anglais

Date Limite Candidature : mercredi 13 juillet 2022

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General information

Reference : UMR7315-ALEBOU-002
Workplace : LIMOGES
Date of publication : Wednesday, June 22, 2022
Scientific Responsible name : Marc Huger
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2022
Proportion of work : Full time
Remuneration : etween 4200€ and 4700€ gross per month depending on the situation of the candidate at the beginning of the contract.

Description of the thesis topic

Sensoring material performance in use, and monitoring using machine learning

This PhD offer (PhD 13) is part of the 15 PhD contract proposals related to the European CESAREF project (www.cesaref.eu). This work, both academic and industrial, aims to characterise and predict in real time the evolution of the performance of refractory materials used in the steel industry.

Objectives: this work aims to implement machine-learning (ML/DL) algorithms in order to predict and anticipate the evolution of the thermochemical and thermomechanical properties of refractory materials used in continuous steel casting processes. This study will be based, on the one hand, on data from non-destructive testing collected by the Vesuvius company and, on the other hand, on the development of a laboratory demonstrator that will be used to define the strategy and architecture of the ML/DL algorithms before implementation on site.

Expected results: A machine-learning algorithm will be trained using data collected in the laboratory and on the Vesuvius company site. This algorithm will be deployed in the form of a digital tool that will make it possible to predict the evolution of the performance of refractory materials on the basis of data collected in real time. This tool will allow the end user to optimally implement the 4R (Reduce, Reuse, Recycle and Replace) decision process.

Skills required: Master's degree or equivalent in materials science and/or materials engineering. Candidates should have excellent skills in materials science (refractories and/or ceramics) and scientific Python programming. Specific competences in machine-learning/deep-learning would be appreciated. Oral and written communication skills (in English) are mandatory.

Please use the recruitment procedure (PhD 05) described on the website portal: https://www.cesaref.eu/recruitment-procedure/

Work Context

Located in Limoges, the IRCER research laboratory (UMR 7315) is affiliated to both the National Center for Scientific Research (CNRS) and the University of Limoges. It is attached to the Institute of Chemistry (INC) of CNRS and all of the works carried out at IRCER are aimed at understanding and controlling the elaboration processes applied to ceramics and surface treatments with a view to producing objects with the optimal properties. The company Vesuvius (www.vesuvius.com) is one of the world's leading companies in molten metal engineering and technology.

As this thesis is part of the European doctoral network Cesaref, the 36-month period will be divided as follows:
- Months 1 to 9 (9 months): the PhD student will initially be based mainly in Ghlin, Belgium on the Vesuvius company site;
- Months 10 to 27 (18 months): the PhD student will then be based in Limoges, France, at the IRCER laboratory (Institut de Recherche sur les Céramiques, UMR CNRS 7315 (www.ircer.fr);
- Months 28 to 36 (9 months): the doctoral student will finally be based again in Ghlin, Belgium, at the Vesuvius company site.
Numerous mobilities are therefore to be expected in accordance with the requirements of this type of European project.

Indicative salary: Between 4200€ and 4700€ gross per month depending on the situation of the candidate at the beginning of the contract.

Position to be filled from 01/10/2022.

Additional Information

This PhD offer (PhD 13) is part of the 15 PhD contract proposals related to the European CESAREF project (www.cesaref.eu). This work, both academic and industrial, aims to characterise and predict in real time the evolution of the performance of refractory materials used in the steel industry.

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