Publisher
source

BRGM

Just Landed

Postdoctoral Researcher in Multimodal Machine Learning for Mineral Particle Fragmentation and Comminution BRGM in France

Degree Level

Postdoc

Field of study

Computer Science

Funding

The position is a temporary, full-time 18-month postdoctoral contract based at BRGM. The employment package includes a salary paid over 13 months, RTT, a company restaurant, sports facilities, vacation and leisure benefits, teleworking, and other work-life-balance advantages. No specific salary amount or tuition funding is stated.

Deadline

Nov 27, 2026

Country flag

Country

France

University

BRGM

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Keywords

Computer Science
Geology
Materials Science
Mathematics
Artificial Intelligence
Computational Science
Computer Vision
Uncertainty Analysis
Mining Engineering
Probabilistic Modeling
Mineral Processing
Multi-task Learning
Statistics
Applied Mathematic
ML

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About this position

BRGM is recruiting a postdoctoral researcher in machine learning for mineral particle fragmentation and comminution. The position is part of the PEPR Sous-sol, bien commun program and the InnovTech project, which brings together eight French research institutions to advance sustainable mineral-resource processing through artificial intelligence and machine learning.

The researcher will contribute to Sub-Task ST3.1.1, focused on connecting elementary ore-fragmentation properties with the performance of comminution technologies. The project addresses the high energy demand of mineral processing by developing a bottom-up methodology that links particle-scale observations with process-scale equipment performance.

The central objective is to learn a compact and transferable “fragmentability signature” for mineral particles. This representation will support predictions of fracture probability, fragment-size distributions, sensitivity to loading regimes, energy consumption, and product-size distributions. The resulting models should enable comparison of comminution-machine options for a given ore and target grind size.

The research uses three complementary data sources: 3D micro-CT volumes describing crack networks, porosity, and mineralogy; single-particle breakage tests measuring fracture energy, breakage probability, and fragment-size distributions; and discrete-element-method simulations capturing fracture mechanisms and energy dissipation.

Research activities include multimodal learning and data fusion, representation learning for complex material systems, probabilistic machine learning and uncertainty quantification, multi-scale predictive modeling, and data-efficient machine learning. Possible approaches include transfer learning, self-supervised learning, surrogate modeling, active learning, and uncertainty-aware decision-making.

The postdoctoral researcher will join the DCGS/GDS unit at BRGM’s technical center in Orléans and collaborate with researchers in data science, applied mathematics, process engineering, and materials science. The role involves leading research activities, publishing in high-impact journals, contributing to project deliverables, and presenting results at international conferences.

Funding details

The position is a temporary, full-time 18-month postdoctoral contract based at BRGM. The employment package includes a salary paid over 13 months, RTT, a company restaurant, sports facilities, vacation and leisure benefits, teleworking, and other work-life-balance advantages. No specific salary amount or tuition funding is stated.

What's required

Applicants must hold a PhD or equivalent in Machine Learning, Artificial Intelligence, Data Science, Applied Mathematics, Computational Statistics, Computer Vision, Scientific Computing, or a closely related discipline, and should be interested in applying advanced machine learning to real-world scientific problems. Desired experience includes machine learning and deep learning; multimodal learning, uncertainty quantification, probabilistic modeling, scientific machine learning, physics-informed learning, hybrid modeling, image analysis, computer vision, geometric data, point clouds, graphs, Python, PyTorch or TensorFlow, reproducible research, model evaluation, benchmarking, and scientific software development. Strong communication and collaboration skills are expected; mineral-processing experience is advantageous.

How to apply

Submit an updated CV and cover letter through the BRGM recruitment portal by 27 November 2026. Shortlisted applicants will be invited to recruitment interviews.

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