Postdoctoral Associate in Computational Chemistry: The Duarte Group at the Chemistry Research Laboratory invites applications for the position of Postdoctoral Research Associate in Computational Chemistry. This role involves research on Machine Learning Interatomic Potentials (MLIPs) for supramolecular modelling, focusing on self-assembly, molecular binding, and catalysis.
Postdoctoral Research Associate in Computational Chemistry
Designation
Postdoctoral Research Associate
| Detail | Information |
|---|---|
| Research Area | Computational Chemistry |
| Location | Chemistry Research Laboratory, UK |
| Pay Scale | RESEARCH GRADE 7 |
| Salary (£) | £39,424 – £47,779 |
| Vacancy ID | 184656 |
| Contact Email | hr@chem.ox.ac.uk |
| Contact Phone | HR Department |
| Closing Date & Time | 18 March 2026, 12:00 |
Eligibility/Qualification
- PhD in computational/theoretical chemistry, physics, or a closely related discipline (or close to completion).
- Strong background in electronic structure methods (e.g., DFT, AIMD), particularly in transition-metal systems.
- Experience in molecular simulation and enhanced sampling techniques.
- Proficiency in Python and familiarity with version control platforms like GitHub.
- Strong research track record demonstrated through peer-reviewed publications.
- Ability to work independently and collaboratively across computational and experimental disciplines.
- Excellent written and oral communication skills.
Preferred Experience:
- Supramolecular chemistry, metal catalysis, or machine learning in chemistry.
- Familiarity with ML approaches for atomistic modelling (e.g., MACE, ACE, NequIP, PhysNet, reactive MD).
- Prior contributions to scientific code or datasets are welcomed.
Job Description
The successful candidate will:
- Lead and manage research on MLIPs for supramolecular modelling.
- Develop and apply advanced electronic structure and molecular simulation methods.
- Work on transition-metal modelling, enhanced sampling techniques, and multiscale approaches.
- Contribute to software development and improvement.
- Analyze data, refine hypotheses, and publish in leading journals.
- Present at international conferences and collaborate with partner institutions.
- Contribute to proposal development, mentor junior researchers, and potentially assist in teaching undergraduate or graduate courses.
How to Apply
Interested candidates should submit a CV and a supporting statement as part of their online application.
Join an ambitious ERC-funded project and help advance predictive modelling at the interface of supramolecular chemistry, catalysis, and machine learning.
Last Date for Application: 18 March 2026, 12:00
