Post-doctoral position in geosciences M/F

CNRS; France; Sur place; EUR 21 000 - 26 000; Plein temps

Résumé du poste

The Earth Sciences Institute of Orléans (ISTO), CNRS, offers a 3-year PhD fellowship to investigate mineral recovery in flotation processes using Computational Fluid Dynamics. The position is located at ISTO in Orléans, France, and is part of the MINFLOT project funded by PEPR.

The successful candidate will develop a robust CFD framework for mechanically agitated flotation reactors, addressing multiphase flow and reactor design across scales in close collaboration with project partners.

Responsabilités

• Develop a robust, multiscale CFD framework for mechanically agitated flotation reactors.
• Investigate multiphase flow, bubble–particle interactions, and particle transport.
• Collaborate within the MINFLOT project to inform models for industrial flotation.

Description du poste

Organisation/Company CNRS Department Institut des Sciences de la Terre d'Orléans Research Field Geosciences Biological sciences Researcher Profile First Stage Researcher (R1) Application Deadline 23 Sep 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The position is located at the Earth Sciences Institute of Orléans (ISTO) in France. ISTO is a joint research laboratory between CNRS, the University of Orléans, and BRGM located on the Geosciences campus of Orléans close to Paris, France. The Porous Media Research Group develops cutting-edge research and worldwide recognized expertise on multi-scale modelling and microfluidic experiments of multiphase flow and reactive transport in geological formations. Our objective is to decipher the mechanisms involved in the remediation of contaminated groundwater, in the underground storage, and in new energy vectors based on the use of the subsurface

Improving mineral recovery efficiency of flotation using Computational Fluid Dynamics

At CNRS, ISTO, We offer a 3-year PhD fellowship to investigate mineral recovery in flotation processes using Computational Fluid Dynamics. The fellowship is part of MINFLOT, a research project funded through the French PEPR “Sous-sol, bien commun” program supported by the Agence Nationale de la Recherche (ANR).
The transition toward a low-carbon economy is driving a rapidly growing demand for critical metals such as lithium, tungsten, cobalt, and nickel. These resources must increasingly be recovered not only from primary ores but also from secondary sources, including mining and processing residues. However, conventional mineral-processing technologies still face significant challenges in terms of recovery efficiency, selectivity, and environmental impact. Improving these processes is therefore essential to enable the sustainable production of critical metals and support the ecological and industrial transition.
Flotation is one of the most widely used and effective techniques for separating valuable minerals from gangue. The process relies on the selective modification of mineral surfaces using chemical reagents, followed by the injection of air bubbles. Hydrophobic mineral particles attach to the bubbles and are transported to the surface, where they can be recovered. The efficiency of flotation depends on a complex interplay between fluid flow, bubble dynamics, particle transport, bubble–particle interactions, and surface chemistry, operating across multiple spatial and temporal scales.
The objective of the PhD thesis is to develop a robust, multiscale CFD framework for mechanically agitated flotation reactors. The research will address the coupled hydrodynamic and physicochemical phenomena governing flotation, with particular emphasis on multiphase flow, bubble–particle interactions, particle transport, and flotation kinetics. High-fidelity simulations at the microreactor scale will be used to develop and inform computationally efficient models suitable for larger, industrial-scale flotation systems. The developed framework will provide predictive insight into mineral recovery and flotation efficiency, while elucidating the influence of reactor design, operating conditions, and process parameters. Ultimately, the work will contribute to the optimization and sustainable intensification of flotation processes, in close interaction with the other multiscale modeling and experimental activities of the MINFLOT project.