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Portal > Offres > Offre UMR3685-PHIDIL-005 - Post-doctorat sur la modélisation (programmation, simulation) des processus physico-chimiques de transformation des minerais de fer H/F

Postdoctoral position on the modelling (programming, simulation) of the physico-chemical processes of iron ore transformation.

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

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General information

Reference : UMR3685-PHIDIL-005
Workplace : GIF SUR YVETTE
Date of publication : Thursday, July 23, 2020
Type of Contract : FTC Scientist
Contract Period : 18 months
Expected date of employment : 2 November 2020
Proportion of work : Full time
Remuneration : 2700
Desired level of education : 5-year university degree
Experience required : 1 to 4 years


*Implementation of new statistical models to deal with the complexity of heterogeneous data sets used in provenance studies of ancient ferrous materials and metals.

-The post-doctorate will contribute to the interdisciplinary project (statistics, archaeometry) " Coupled model for the restitution of ferrous metal exchange networks in ancient societies", funded by the Field of Major Interest (DIM) Ancient and Heritage Materials.
-The final objective is to develop a new statistical formalism to connect the chemistry measured in ores, slags found on production sites, and those of objects (through the slag inclusions found in the metal).
-This formalism will be based on simulations of physical processes and Monte-Carlo method to determine the probabilities of matching of objects and ancient sites. More generally, it seeks to lay the foundations of a model for the restitution of trade routes for ferrous materials in a systemic framework.
-This development will make it possible to consider the question of data coupling that is involved in the description of exchange networks.


-Programming of the main parameters (modeling, code, simulation) of the global origin attribution model.
1/ Modelling of the main physico-chemical processes from the transformation of the raw materials (ore, charcoal, furnace walls) in the reduction furnace of ancient metallurgy to the resulting slag wastes, and slag inclusions trapped in the metal of the object.
2/ Application of the model (programming of simulation) on a variety of ores and process details covering a wide range of physical and chemical conditions of the process as a whole.
3/ This modeling approach will be used in conjunction with machine learning techniques or Markov chain Monte Carlo (MCMC) methods in order to probabilistically relate ferrous material and provenance, and eventually build a supervised learning system specific to the field of application of ferrous material provenance.

-Activity report
Writing of research and synthesis reports.
Participation in meetings and conferences.


-The candidate will have defended a thesis in physics or applied mathematics, with strong skills in simulation, Python programming and MCMC writing.
-He/she will also be required to work in collaboration with the partner teams (APC, LAPA-NIMBE, ICMPE, EFEO) and with the supervision of the project researchers.
-He/she will be in charge of writing research and synthesis reports.
-Skills in presentation and dissemination of results.
-An open-mindedness towards interdisciplinarity (archaeometry) is also required.

Work Context

The post-doctorate position will mainly be based at the AstroParticle and Cosmology Laboratory (UMR 7164, Université de Paris, Bâtiment Condorcet, Paris 13), where he/she will be able to work in collaboration with the "Cosmology" group, which applies methods such as Bayesian inference, Markov chain Monte Carlo, machine learning, to interdisciplinary themes. He/she will also work at the Archeomaterials and Alteration Prediction Laboratory LAPA-NIMBE (UMR 3685, CEA Saclay, 91191 Gif-sur-Yvette) which has the knowledge of the physical processes of the ancient iron chaîne opératoire as well as the interdisciplinary databases for the calibration of the model and the implementation of the methodology of provenance of ancient ferrous metals.

Eric Aubourg (APC, Université Paris Diderot)
Stéphanie Leroy (LAPA-NIMBE, IRAMAT, CEA Saclay)
Anita Quiles (IFAO, chercheur associé APC)

Constraints and risks


Additional Information


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