En poursuivant votre navigation sur ce site, vous acceptez le dépôt de cookies dans votre navigateur. (En savoir plus)
Portail > Offres > Offre UMR5216-VIRFAU-025 - (H/F) : Post-Doc : Prédiction des Effets d'Anode dans la production d'aluminium

(M/F) : Post-Doc : Anode Effects Prediction in Aluminum Production

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

Date Limite Candidature : jeudi 26 mai 2022

Assurez-vous que votre profil candidat soit correctement renseigné avant de postuler. Les informations de votre profil complètent celles associées à chaque candidature. Afin d’augmenter votre visibilité sur notre Portail Emploi et ainsi permettre aux recruteurs de consulter votre profil candidat, vous avez la possibilité de déposer votre CV dans notre CVThèque en un clic !

General information

Reference : UMR5216-VIRFAU-025
Date of publication : Thursday, March 24, 2022
Type of Contract : FTC Scientist
Contract Period : 24 months
Expected date of employment : 1 November 2022
Proportion of work : Full time
Remuneration : 2 663, 79 € monthly gross
Desired level of education : PhD
Experience required : 1 to 4 years


Aluminum metal is industrially produced by electrolysis in an anhydrous medium, at high temperature (close to 1000°C). This process, called Hall-Héroult, consists in dissociating alumina Al2O3 by electrolysis in a cryolite-based bath (mixed fluoride of aluminum and sodium). During the electrolysis reaction, the aluminum is generated in liquid state and accumulates on the surface of the cathode at the bottom of the pot.
For this reaction to take place, alumina must be present in sufficient quantity in the cryolite bath. When this does not happen, the pot switches to a different electrochemical reaction, which consumes much more energy, resulting in a significant voltage increase. The transition from nominal to high voltage is very abrupt (of the order of a few seconds) which makes it difficult to anticipate its occurrence. This phenomenon, called the anode effect, is therefore very harmful and its prevention highly desirable.
This project aims to predict and anticipate pathological behaviors dues to anode effects in order to avoid or treat them in advance. This project aims to predict certain anode effects several minutes before they spread to the whole pot, by analyzing anode current measurements and other process monitoring parameters.
The primary goal is to obtain on-line estimates of the alumina concentration values present below each anode, from the measured signals and using the known relationships between ACD (anode-cathode distance), alumina concentration and anode resistance. The alumina concentration, in fact, is not homogeneous in the cryolithic bath, due to diffusion and convection phenomena and to local injections of alumina in a powder state. In addition, the local concentration value is also function of the current efficiency of each anode.
By using, therefore, the knowledge of the relationship between resistance, ACD and alumina and also the dynamics of ACD and alumina, which amount to conservation laws, one could design estimators of the local concentration of alumina and thus use them for the prediction of low values, which could cause anode effects in the pot. From the results of the predictions, the local alumina dosage could then be preventively adjusted in order to minimize or eliminate the disturbances caused by the anode effect.


The post-doc researcher will be hosted for 50% of his working time in the Rio Tinto laboratories, at the establishment's headquarters in Voreppe and at the LRF research center in Saint Jean de Maurienne, and 50% of the time at GIPSA -lab.
With Rio Tinto, he will take care of
• the management of the pot data necessary for the study,
• the coordination with Rio Tinto members on technical aspects relating to the pot,
• the collaboration in setting up tests on the APXe pot.
The post-doc researcher, during his periods at GIPSA-lab, will take care of
• the formalization of identification, observation and control problems,
• their coding and resolution through optimization and learning tools,
• the consulting with colleagues from GIPSA-lab on methodological and theoretical aspects.


- PhD in control or related field
- Experience in control applied to chemical processes
- Skills with Python and Matlab: Programming of numerical simulators of pot cell dynamics and resolution of optimization problems (matlab/python), processing of acquired data (python, pandas) and application of machine learning algorithms for regression and the classification of estimated trajectories (python, sklearn).

Work Context

Gipsa-lab is a CNRS research unit joint, Grenoble-INP (Grenoble Institute of Technology), University of Grenoble under agreement with Inria, Observatory of Sciences of the Universe of Grenoble. With 350 people including about 150 doctoral students, Gipsa-lab is a multidisciplinary research unit developing both basic and applied researches on complex signals and systems. Gipsa-lab develops projects in the strategic areas of energy, environment, communication, intelligent systems, life and health and linguistic engineering.
Thanks to the research activities, Gipsa-lab maintains a constant link with the economic environment through a strong partnership with companies. Gipsa-lab staff is involved in teaching and training in the various universities and engineering schools of the Grenoble academic area (Université Grenoble Alpes). Gipsa-lab is internationally recognized for the research achieved in Automatic & Diagnostics, Signal Image Information Data Sciences, Speech and Cognition. The research unit develops projects in 16 teams organized in 4 Reseach centers
.Automatic & Diagnostic
.Data Science
.Geometry, Learning, Information and Algorithms
.Speech -cognition
Gipsa-lab regroups 150 permanent staff and around 250 no-permanent staff (Phd, post-dotoral students, visiting scholars, trainees in master…)

The post-doctoral researcher will join the MODUS team at GIPSA-lab, under the supervision of the scientific directors.

Constraints and risks


We talk about it on Twitter!