At a glance

Location: Saint Quentin Fallavier, France
Work type: Onsite
Category: Engineering

Location: Saint Quentin Fallavier, FR, 38291

R&D Engineer Intern - Ecopact 2.0/Biochar

Localisation

Saint Quentin Fallavier, FR, 38291

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Numéro d'emploi

19868

JOB DESCRIPTION

Job Title

Internship offer

R&D Engineer Intern

Ecopact 2.0 / Biochar

Business Unit and Location

Holcim Innovation Center, Saint-Quentin-Fallavier

Department

Building Systems

WHO IS HOLCIM?

Holcim is the leading partner for sustainable construction with net sales of CHF 15.7 billion in 2025, creating value across the built environment from infrastructure and industry to buildings. Headquartered in Zug, Switzerland, Holcim has more than 50 000 employees in 45 countries – across Europe, Latin America and Asia, Middle East & Africa – and has been recognized as a Global Top Employer by the Top Employers Institute. Holcim offers high-value end-to-end Building Materials and Building Solutions, from foundation and flooring to walling and roofing – powered by premium brands including ECOPact, ECOPlanet, ECOCycle, and Ytong.

WHO ARE HOLCIM PEOPLE?

Holcim people are passionate about finding better ways to build. They embrace innovation and improvement with a pioneering spirit. They work as trusted partners, creating better solutions and experiences for their customers, communities, and colleagues.

YOUR HOLCIM EXPERIENCE

At Holcim, there are endless opportunities for you to play your part. Whether you’re in a technical, managerial, or frontline role, you can shape a career that works for you. With us you’ll have the chance to embrace the passion we share for our planet. You’ll be encouraged to seek out diverse perspectives, share your ideas and build the skills and connections you need to perform at your best. Because it’s only when we work together in a culture where everyone thrives that we can build the world we all want to live in. To find out more, visit www.holcim.com/careers.

THE OPPORTUNITY – CONTEXT OF THE MISSIONS

Decarbonizing the construction industry requires accelerating the adoption of low-carbon binders, notably slag-blended cements. Accurately predicting the long-term deformation and viscoelastic behavior (creep) of these materials is essential for reliable structural design.

This 6-month research internship aims to investigate the long-term creep behavior of low-carbon cement pastes by bridging micro-mechanical testing with advanced predictive modeling. The intern will combine experimental characterization and data-driven methods to improve the predictive accuracy of concrete creep models for next-generation binders.

MISSIONS

During the 6-month internship, you will contribute to the following research steps:

1. State of the art & data preparation

Review scientific literature on slag hydration kinetics, microstructure development, and creep mechanisms.

consolidate and analyze experimental creep databases (literature and internal test series).

2. Microindentation test

Prepare cement paste specimens and conduct microindentation testing to characterize local viscoelastic properties.

Process experimental indentation curves to extract micro-mechanical creep parameters.

3. Predictive modeling

Implement and work with state-of-the-art concrete creep models (e.g., Bažant B4).

Evaluate the integration of experimental micro-mechanical data and Machine Learning algorithms (e.g., Gaussian Processes, Random Forest) to enhance model calibration across diverse mix formulations.

4. Reporting

Benchmark model predictions against macroscopic experimental creep datasets.

Conduct parametric sensitivity analyses on key binder variables and synthesize findings into a comprehensive technical report / master’s thesis.

ABOUT YOU

REQUIRED SKILLS

Hard skills

Strong programming skills in Python and Machine Learning framework

Solid background un material mechanics, concrete behavior or microindentation techniques

Soft skills

Analytical mindset and scientific rigor

Autonomy in managing a hybrid project combining experimental testing and numerical modeling

Good communication skills to translate complex data into user-friendly tools

Languages: Fluency in English (written and spoken) for technical reporting and operating in an international R&D environment

EDUCATION LEVEL / TRAINING

Grand School engineering student or currently pursuing a Master’s degree (Bac +5) in Civil Engineering, Materials Science, Computational Mechanics, or Data Science for Materials