Internship - Modeling and Predicting the Composition of Textile Waste Streams

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 intern’s main responsibilities will include:

Identifying and analyzing available data (characterization campaigns, results of industrial or pilot tests, bi