Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : CRIStAL UMR 9189 – Lille
Durée : 36 months
Contact : pierre.chainais@centralelille.fr
Date limite de publication : 2020/04/30
Contexte :
This PhD project is at the interface between artificial intelligence and chemistry using robots. It will take place within a collaboration between 2 labs that are CRIStAL, UMR 9189, and UCCS, UMR 8181, a chemistry lab in Lille.
Supervisors are :
– Pierre Chainais, CRIStAL, UMR 9189, Centrale Lille ;
– Sébastien Paul, UCCS, UMR 8181, Centrale Lille
->prenom.nom AT centralelille.fr
In chemistry, the discovery of new reactions and processes often relies on a big amount of exploratory experiments inspired by a lot of expert knowledge. This experimental design is even more crucial when looking for new catalysts. Catalysts are material that tend to favor and accelerate certain chemical reactions, sometimes by a tremendous factor. Applications are omnipresent, with a strong impact on crucial domains such as environment, food, health, energy, to cite a few only.
The design of a new catalyst comprises the systematic exploration of sample libraries that must be synthesized, analysed and tested for a targeted reaction of interest. High-throughput catalytic screening uses robots to take advantage of the parallelization and automation of these operations.
This is precisely what the Equipex REALCAT (Advanced High-Throughput Technologies Platform for Biorefineries Catalysts Design, www.realcat.fr) permits to carry out. This platform, located at Centrale Lille, is managed by the University of Lille and coordinated by the Unit of Catalysis and Solid State Chemistry (UCCS UMR 8181, http://uccs.univ-lille1.fr) with a set of partners including CRIStAL laboratory (UMR 9189, https://www.cristal.univ-lille.fr) and the Charles Viollette Institute (ICV UMR INRA 1281, http://institutcharlesviollette.com).
The project will aim at exploiting the richness of existing data from previous and current experiments to optimize the future behaviour of REALCAT through an intelligent research system. The PhD student will be co-supervised by experienced researchers from UCCS and CRIStAL labs. During the course of the PhD a secondment will be done in Shanghai, China, in the E2P2 laboratory, which is a mixed unit between CNRS and the SOLVAY company.
This grant is supported by the European programme PEARL, see www.pearl-phd-lille.eu .
Net salary & lump costs : A net salary of about €1,600 + €530 per month to cover mobility, travel and family costs.
Sujet :
Supervisors
Pierre Chainais, CRIStAL, UMR 9189, Centrale Lille ;
Sébastien Paul, UCCS, UMR 8181, Centrale Lille
prenom.nom AT centralelille.fr
Project
This PhD project is at the interface between artificial intelligence and chemistry using robots. In chemistry, the discovery of new reactions and processes often relies on a big amount of exploratory experiments inspired by a lot of expert knowledge. This experimental design is even more crucial when looking for new catalysts. Catalysts are material that tend to favor and accelerate certain chemical reactions, sometimes by a tremendous factor. Applications are omnipresent, with a strong impact on crucial domains such as environment, food, health, energy, to cite a few only.
The design of a new catalyst comprises the systematic exploration of sample libraries that must be synthesized, analysed and tested for a targeted reaction of interest. High-throughput catalytic screening uses robots to take advantage of the parallelization and automation of these operations.
This is precisely what the Equipex REALCAT (Advanced High-Throughput Technologies Platform for Biorefineries Catalysts Design, www.realcat.fr) permits to carry out. This platform, located at Centrale Lille, is managed by the University of Lille and coordinated by the Unit of Catalysis and Solid State Chemistry (UCCS UMR 8181, http://uccs.univ-lille1.fr) with a set of partners including CRIStAL laboratory (UMR 9189, https://www.cristal.univ-lille.fr) and the Charles Viollette Institute (ICV UMR INRA 1281, http://institutcharlesviollette.com).
This platform is able to synthesize catalysts as well as to test their reaction performance and to characterize them at high-speed on a large set of robots. Any kind of catalyst (chemo- or bio-catalysts and even the novel concept of hybrid catalysts combining both types) can be considered on REALCAT. The development chain is gathered on the same site, which makes this platform unique in the world. The automated exploration generates a large amount of data that must then be formatted, analysed and exploited to optimize the quest for new catalysts and protocols.
The objective of the AICAT project is to develop a machine learning approach capable of establishing rapidly the correspondence between the input data of the system (i.e. synthesis conditions or physicochemical properties of the catalysts for example) and the output data (activity or yield into the molecules of interest for example). A better understanding of the input-output relation will be exploited to speed up the discovery of the optimal catalyst for a given reaction through the rational selection of the most efficient synthesis conditions, taking the best benefit from REALCAT power.
The project will aim at exploiting the richness of existing data from previous and current experiments to optimize the future behaviour of REALCAT through an intelligent research system. The PhD student will be co-supervised by experienced researchers from UCCS and CRIStAL labs. During the course of the PhD a secondment will be done in Shanghai, China, in the E2P2 laboratory, which is a mixed unit between CNRS and the SOLVAY company.
In this multidisciplinary context, the PhD student must be skilled in data treatment, artificial intelligence and machine learning, but also strongly interested in green chemistry and catalysis.
Net salary & lump costs : A net salary of about €1,600 + €530 per month to cover mobility, travel and family costs.
Application procedure (applicant should have spent less thant 12months in France since sept. 2017)
The application procedure is detailed on the European programme PEARL website www.pearl-phd-lille.eu. The funding is managed by the I-SITE ULNE foundation which is a partnership foundation between the University of Lille, Engineering schools, research organisms, the Institut Pasteur de Lille and the University hospital.
The application file will have to be submitted before April 15, 2020 (10h Paris Time) and emailed to the following address : international@isite-ulne.fr
Profil du candidat :
This grant is submitted to some restrictions. The applicant should not have spent more thant 12 months in France since Sept. 2017.
This interdisciplinary project necessitates good scientific skills in general. T
Formation et compétences requises :
A Master level in machine learning, signal processing, applied mathematics, or statistics is expected. Programming skills and an interest for experimental chemistry are welcome.
Adresse d’emploi :
Application procedure (applicant should have spent less thant 12months in France since sept. 2017)
The application procedure is detailed on the European programme PEARL website www.pearl-phd-lille.eu. The funding is managed by the I-SITE ULNE foundation which is a partnership foundation between the University of Lille, Engineering schools, research organisms, the Institut Pasteur de Lille and the University hospital.
The application file will have to be submitted before April 15, 2020 (10h Paris Time) and emailed to the following address : international@isite-ulne.fr
Document attaché : PhD_AICAT_2020.pdf