Post-Doc in Computational chemistry applied to heterogeneous catalysts

Updated: 26 days ago
Location: Solaize, RHONE ALPES
Job Type: FullTime
Deadline: 15 Sep 2024

3 Apr 2024
Job Information
Organisation/Company

IFP Energies nouvelles (IFPEN)
Research Field

Chemistry » Computational chemistry
Chemistry » Heterogeneous catalysis
Researcher Profile

Recognised Researcher (R2)
Country

France
Application Deadline

15 Sep 2024 - 14:26 (Europe/Paris)
Type of Contract

Temporary
Job Status

Full-time
Hours Per Week

35
Offer Starting Date

1 Oct 2024
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

A fully funded post-doc position will be open at IFP Energies Nouvelles (Lyon, France) in Autumn 2024, under the supervision of Pascal Raybaud, for a duration of 12+6 months.

Title: Computational screening of heterogeneous catalysts for the syngas to alcohols reaction

 Subject: The synthesis of higher alcohols (with more than 2 carbons) from syngas (CO+H2 ) –produced itself from biomass – represents a crucial interest for various applications such as medical chemistry, plastics industry, fuel additives (sustainable aviation fuels). Although various catalytic materials, such as molybdenum disulfides (MoS2 ), have been experimentally reported, observed performances are still below the targeted ones. To overcome this, a more rational approach based on density functional theory (DFT) and structure-activity correlations must be built to explore new materials.

The post-doctoral research project will aim first at identifying, using state-of-the-art DFT, the key limiting steps of the mechanisms among the various elementary ones involved in the reaction: C-O bond scission vs. C-C coupling. As a reference case study, MoS2 catalytic sites will be chosen to benchmark this reaction and to quantify relevant thermodynamic and kinetic descriptors. From this knowledge, a smart methodology (including machine learning) will be established to screen various dopants for MoS2 catalysts and identify potential materials with improved selectivity and activity.

Context: The post-doctoral researcher will benefit from a multidisciplinary environment within the framework of the Optisfuel project supported by PEPR B-BEST (Grant ANR-22-PEBB-0011).

How to apply: Motivated candidates (having defended their PhD thesis within the past 3 years) are invited to send a letter of motivation, a CV and 2 letters of recommendation to the following contact: [email protected]

Selected references from the group can be viewed on: https://www.ifpenergiesnouvelles.com/page/pascal-raybaud


Requirements
Research Field
Chemistry » Computational chemistry
Education Level
PhD or equivalent

Skills/Qualifications

Skills: The candidate must have a strong background in theoretical chemistry. Strong skills with quantum computational codes, Python scripting, and machine learning approaches are expected. A good knowledge of catalysis concepts will be welcome.


Languages
ENGLISH
Level
Excellent

Languages
FRENCH
Level
Basic

Additional Information
Eligibility criteria

Candidates must have defended their PhD thesis within the past 3 years (not latter)


Selection process

Motivated candidates are invited to send a letter of motivation, a CV and 2 letters of recommendation to the following contact: [email protected]

 


Website for additional job details

https://www.ifpenergiesnouvelles.com/page/pascal-raybaud

Work Location(s)
Number of offers available
1
Company/Institute
IFP Energies nouvelles
Country
France
City
Solaize
Postal Code
69360
Street
Rond-point de l'échangeur de Solaize
Geofield


Where to apply
E-mail

[email protected]

Contact
City

Rueil-Malmaison
Website

http://www.ifpenergiesnouvelles.com/
Street

4 avenue de Bois-Préau
Postal Code

92852

STATUS: EXPIRED