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Post-doc (deadline June 30!): DFT-Modeling of De ... (1 reply)
Dear Professor,
Herewith I would like to submit my applications for the Post-Doctor position in your research group. My research interest covers the investigation of designing efficient, stable, and non-toxic perovskite solar cells (PSCs) by using state-of-the-art density functional theory (DFT) calculations and I published 16 papers including 2 papers in Journal of materials Chemistry A (Impact factor > 9.9), 3 papers in Physical review B as the first author.
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Background: Digitalization has emerged in recent years with the potential to revolutionize the field of industrial catalysis.[1] The combination of high throughput experimentation and computation with artificial intelligence (AI) techniques is expected to lead to significant time savings in the development of industrial catalysts, a clear shift away from the often decades-long development cycles of many industrial catalysts in operation today.
Computational chemistry (mainly density functional theory, DFT) is an integral part of modern catalysis research. Scaling relations correlating the adsorption energies of adsorbates with the performance of catalysts allow the screening of large numbers of catalysts, before they are even synthesized.[2] We have been particularly active in this field,[3] based on our strong expertise in the modeling of industrially relevant heterogeneous catalysts.
Vacancy description: In tight collaboration with its industrial partner E2P2L-SOLVAY-CNRS based in Shanghai, the group of Dr. Carine Michel (ENS Lyon, France) is looking for a post-doctoral researcher to develop scaling relationships and other descriptors for industrially relevant catalytic hydrogenation, oxidation, and amination reactions. The data generated by the modeling will be combined with experimental catalyst testing and characterization data generated in Shanghai, and analyzed by AI techniques to predict improved generations of catalysts.
The successful candidate is expected to have strong experience in the application of DFT methods in heterogeneous catalysis or materials science. Knowledge of artificial intelligence techniques is not mandatory but considered a strong plus.
Job location: Chemistry Laboratory of ENS Lyon (France) with short stays at Solvay Shanghai.
Duration: 12 months
Important condition: due to funding modalities (http://cnrsbeijing.cnrs.fr/k-c-wong2019/), the candidate must be a mainland China citizen currently employed by a scientific or academic institution in China.
Interested candidates not meeting this requirement are still invited to apply since similar openings in our group may open up in the near future.
Application deadline: due to the tight deadline (June 30, 2019, potentially to be extended by a few days) interested candidates are requested to immediately contact Dr. Carine Michel ([email protected]) or Dr. Raphael Wischert ([email protected]).
[1] a) R. Schlögl, ChemCatChem 2017, 9, 533-541; b) G. Jones, Nature Catalysis 2018, 1, 311-313.
[2] a) J. K. Norskov, T. Bligaard, J. Rossmeisl, C. H. Christensen, Nat Chem 2009, 1, 37-46; b) J. W. Medlin, M. M. Montemore, Nat Chem 2015, 7, 378-380.
[3] a) F. Calle-Vallejo, D. Loffreda, T. M. KoperMarc, P. Sautet, Nat Chem 2015, 7, 403-410; b) T. Wang, Z. Yan, C. Michel, M. Pera-Titus, P. Sautet, ACS Catal. 2018, 8, 63-68.