JOB DESCRIPTION

About us:

Reju is an industrial company specializing in the development of advanced textile recycling solutions, with the goal of contributing to the transition toward a large-scale circular textile economy. Reju focuses specifically on the recycling of post-consumer polyester, developing technologies and value chains capable of transforming complex textile waste into high-quality recycled raw materials that can be reused in new textile applications.

The company operates at the intersection of technological innovation, industrial data, and partnerships with value chain stakeholders (collection, sorting, recycling, brands, institutions). In this context, a detailed understanding of textile waste streams—their composition, variability, and availability—is a key strategic lever for guiding technological, industrial, and economic decisions.

About the mission we offer you:

As part of efforts to develop chemical recycling pathways for textiles and improve sorting and recovery performance, a detailed understanding of the composition of textile waste streams is a key challenge. Today, a wealth of characterization data (material analyses, sorting campaigns, pilot tests, data from sorting centers or R&D projects) exists, but it is often scattered and rarely used for predictive purposes.

Internship Objective

The objective of the internship is to develop a structured database model capable of leveraging existing characterization data and test results to predict the composition of textile waste streams (fibers, blends, contaminants, forms, origins, etc.) based on various input parameters (geographic area, collection type, seasonality, product type, etc.).

Main Responsibilities

The interns main responsibilities will include:

• Identifying and analyzing available data (characterization campaigns, results of industrial or pilot tests, bibliographic and internal data).
• Define a database structure tailored to textile streams (variables, levels of granularity, data quality).
• Establish a methodology for data processing and cleaning (statistical analysis, handling of biases and missing data).
• Develop an exploratory predictive model (statistical or data-driven) to estimate the composition of waste streams based on available input data.
• Test and analyze the models robustness, identify its limitations, and propose areas for improvement.
• Present the results in the form of summary reports, tables, and visualizations, with a focus on industrial applications.

Skills developed

• Management and structuring of technical databases
• Data analysis and applied statistics
• Modeling and predictive approaches
• Understanding of textile waste streams and the challenges of the circular economy
• Working at the intersection of data, industrial processes, and strategic decision-making

About you:

We love to hear from you and how you match with this position. To be successful in this mission you should consider the following requirements:

Second-year engineering student (industrial engineering, data engineering, materials engineering, chemical engineering, process engineering, or equivalent), with an interest in data analysis, industrial challenges, and the circular economy. Prior experience in data processing (Python, advanced Excel, SQL, or equivalent) is a plus.

Your career with us

Working at Technip Energies is an inspiring journey, filled with groundbreaking projects and dynamic collaborations. Surrounded by diverse and talented individuals, you will feel welcomed, respected, and engaged. Enjoy a safe, caring environment where you can spark new ideas, reimagine the future, and lead change. As your career grows, you will benefit from learning opportunities at T.EN University, such as The Future Ready Program, Graduate Program, and from the support of your manager through check-in moments like the Mid-Year Development Review, fostering continuous growth and development.

Whats Next?

Once receiving your system application, our recruiting team will screen and match your skills, experience, and potential team fit against the role requirements. We ask for your patience as the team completes the volume of applications with reasonable timeframe. Check your application progress periodically via personal account from created candidate profile during your application.

We invite you to get to know more about our company by visiting www.ten.com and follow us on LinkedIn, Instagram, Facebook, X and YouTube for company updates.