Towards an analytical strategy for tracking PFAS in recycling processes

Do you want to contribute to the environmental transition and take on a major scientific challenge? This PhD project offers the opportunity to develop innovative solutions for a critical issue: the sustainable recycling of textiles and batteries. These strategic sectors are confronted with the presence of PFAS, persistent fluorinated substances that pose significant health and environmental risks. Managing these contaminants is essential to ensure the efficiency and safety of recycling processes, as well as the quality of recycled products. The project aims to design a comprehensive analytical strategy to identify, quantify, and monitor PFAS across all recycling streams. You will combine advanced analytical techniques tailored to the complexity of the matrices and the chemical diversity of PFAS, including optimized extraction methods, coupling of separation techniques with high-resolution tandem mass spectrometry, inductively coupled plasma mass spectrometry (ICP-MS), and advanced data processing approaches. This PhD project will provide unique expertise in analytical chemistry applied to emerging contaminants and will directly contribute to the sustainability and safety of recycling processes. It offers the opportunity to participate in innovation in PFAS characterization and in managing associated risks in complex industrial matrices.
 

IFP Energies nouvelles is a French public-sector research, innovation and training center. Its mission is to develop efficient, economical, clean and sustainable technologies in the fields of energy, transport and the environment. For more information, see our WEB site. 
IFPEN offers a stimulating research environment, with access to first in class laboratory infrastructures and computing facilities. IFPEN offers competitive salary and benefits packages. All PhD students have access to dedicated seminars and training sessions. 
 

Academic requirements    University Master degree in analytical sciences    
Language requirements    English level B2 (CEFR)  
Other requirements    Background in analytical sciences, with a strong interest in experimental work and complex data processing.