AI-Driven Energy Storage Materials Engineer

IMT Mines Albi; France; On-site; EUR 40,000 - 54,000; Full time

Job summary

IMT Mines Albi, within the RAPSODEE Center, invites applications for a Postdoctoral Researcher position in Chemical Engineering and energy storage materials. The ERC Advanced Grant project focuses on biocarbon composites and AI-assisted design, in an international research environment with collaborations in the USA and India.

The successful candidate will develop computational models, data-driven methods, and experimental validation to improve storage capacity and safety of novel energy storage

Qualifications

• PhD degree in a related field (Chemical Engineering, Materials Science, Energy Engineering, Physics, Computational Science).
• Strong background in computational science, machine learning and AI-driven methods.
• Good programming skills.

Responsibilities

• Design and develop advanced energy storage materials and devices using computational methods, AI, and experiments.
• Develop and apply computational models, data-driven methods, and AI-assisted tools to predict properties and optimize materials.
• Integrate theoretical and computational work with experimental synthesis, characterization, validation and optimization of storage solutions.
• Investigate thermophysical, thermomechanical, and thermal stability properties of graphitic-based biocarbon composites.
• Explore relationships between material structure and device performance to enable safe and sustainable energy storage technologies.

Skills

Computational science

Machine learning

AI-driven methods

Education

PhD in Chemical Engineering, Materials Science, Energy Engineering, Physics, Computational Science

Tools

Python

MATLAB

Job description

IMT Mines Albi, within the RAPSODEE Center, invites applications for a Postdoctoral Researcher position in Chemical Engineering and energy storage materials. The ERC Advanced Grant project focuses on biocarbon composites and AI-assisted design, in an international research environment with collaborations in the USA and India.

The successful candidate will develop computational models, data-driven methods, and experimental validation to improve storage capacity and safety of novel energy storage