Postdoc position in prebiotic chemistry - computational

Institut de Physique du Globe de Paris; France; Sur place; EUR 35 000 - 45 000; Plein temps

Résumé du poste

A leading research institution in France is seeking a postdoctoral researcher to join the ab initio team. The role involves computational studies on prebiotic reactions between organic molecules and lava surfaces, leveraging density-functional theory and molecular dynamics. Candidates should have a PhD and strong experience in computational chemistry, machine learning, and programming, with excellent communication skills. This is an exciting opportunity to contribute to cutting-edge research in organic chemistry and catalysis.

Qualifications

• Strong background in computational chemistry or physics with experience in catalytic research.
• Knowledge in programming languages such as Python is essential.
• Excellent communication skills and proven ability to work independently.

Responsabilités

• Conduct atomistic simulations based on density-functional theory.
• Explore catalytic potential of amorphous structures of fresh lavas.
• Fit machine-learning interatomic potentials and run large-scale simulations.

Connaissances

Computational chemistry

Machine learning techniques

Molecular dynamics simulations

Statistical physics techniques

Programming languages (Python)

Formation

PhD or equivalent

Description du poste

Offer Description

An opening at the postdoctoral level is available in the ab initio team of IPGP to work on the prebiotic reactions between simple organic molecules and the surface of fresh warm lavas. The work is entirely computational.

The position is on the project VOLCANOR, funded by the HERMES inidex initiative of the Université Paris Cité.

The successful candidate will perform an ensemble of atomistic simulations based on density‑functional theory and molecular dynamics. She/he will explore first the catalytic potential of the amorphous structure exhibited by fresh lavas. Then, she/he will fit machine‑learning interatomic potentials, and will further run large‑scale atomistic simulations to study the possible chemical reactions mediated by the surface. Particular reactions that mark the transition from prebiotic to biotic chemistry will be thoroughly investigated.

Where to apply

E‑mail: [e-mail]

Requirements

• Research Field: Chemistry
• Education Level: PhD or equivalent
• Strong background in computational chemistry or physics, with experience in catalytic research and organic chemistry, machine‑learning potentials, molecular dynamics simulations, and statistical physics techniques.
• Strong knowledge of thermodynamics, mineral physics, or organic chemistry.
• Strong knowledge of programming languages such as Python and other machine‑learning techniques.
• Excellent communication skills and ability to work well in a team environment, work independently, manage time effectively, and show a strong interest in continuing research in organic chemistry, catalysis, and prebiotic chemistry.
• Only candidates with a strong background and experience in computational chemistry or solid‑state physics will be considered. Experience with machine learning is essential.
• Languages: English – Excellent level.
• Years of research experience: 1–4.