Hosting structure

Université PSL is launching a call for applications for a Junior Professor Chair in Applied Artificial Intelligence (AI), titled “AI for analysis and interpretation of structural data for materials and soft matter”. The activity will take place in École Supérieure de Physique et Chimie Industrielle (ESPCI) in Paris, Université Paris Sciences et Lettres.

This is a tenure track position with a reduced teaching load leading to a full professor position at PSL University with research and teaching affiliation at the ESPCI. The position will start on February 2027 (or at a mutually agreed later date). The contract must be signed by the end of December 2026.

Depending on the candidate’s profile, the successful applicant will join either the Chemistry, Macromolecular Chemistry and Materials Laboratory (C3M), a joint CNRS–ESPCI research unit (UMR 7167), or the Soft Matter Science and Engineering Laboratory (SIMM), a joint CNRS–ESPCI research unit (UMR 7615). The recruited researcher will also be functionally affiliated with MINGUS (Machine Intelligence Group for the Sciences), the ESPCI research team dedicated to artificial intelligence for science, directed by Alexandre Allauzen. This flexibility is intended to ensure the best possible fit for the selected candidate, depending on their profile: whether it is a candidate coming from an AI background who will work on materials characterization, or conversely a candidate with a materials science background seeking to develop AI approaches.

The position is open to all researchers wishing to develop their activity in AI applied to the analysis and design of materials. The position includes an internationally competitive salary and competitive start-up package.

Wholly committed to excellence in education, training and research, PSL is a global university, which aims to reflect, represent and influence society today and the world of the future in all its diversity. The university’s collegial ethos is a major asset. Made up of thirteen component institutions such as ESPCI, PSL ensures that dialogue takes place between all areas of knowledge, innovation and creativity in science, humanities, social sciences, arts and engineering. PSL offers an education led by the research carried out in its laboratories while encouraging discussion and mobility between disciplines and across schools. Our university exercises critical thinking and fosters creativity. Students are selected on the basis of their potential and talent. The university champions equal opportunities and promotes social, cultural and geographic diversity, and students are guaranteed individual mentoring, small class sizes and personalized academic pathways.

Presentation of the host laboratory:
Depending on the profile of the candidate, the appointment may be made within one of two CNRS research laboratories. The C3M Laboratory (Molecular, Macromolecular Chemistry and Materials) designs, synthesizes, and investigates new molecules and materials, with a particular focus on the structure-property correlation. Its research activities focus on catalysis, sustainable chemistry, recyclable and self-healing materials, and reactive processing technologies. This joint CNRS research unit is organized into three research groups, forming a continuum of expertise that is both well established and internationally recognized in the fields of molecular and macromolecular synthesis, as well as the physical chemistry of soft matter. The SIMM laboratory (Soft Matter Science and Engineering) brings together in the same lab chemists, physical chemists, and physicists to address the complexity of soft matter systems (materials and fluids). Soft matter is difficult to apprehend because of its heterogeneous, disordered, and dissipative nature, making the relationship between structure and properties complex. The SIMM laboratory addresses this challenge and is internationally recognized for its multidisciplinary approach, combining the design of precisely controlled chemical architectures with state-of-the-art experimental characterization techniques and advanced modeling tools to understand and engineer soft matter.

Given the interdisciplinary nature of the position, the successful candidate will also be affiliated with the MINGUS team (Machine Intelligence Group for the Sciences), which specializes in the development of machine learning algorithms and methods for scientific applications. The purpose of this dual affiliation is to provide access to a unique research environment that fosters methodological advances at the intersection of artificial intelligence, data analysis, and materials discovery and design.