Postdoctoral Research Associate

About the role

Applications are invited for a 2.5‑year fixed-term position in the group of Dr Francisco Martin‑Martinez in the Department of Chemistry, King’s College London, in co-supervision with Dr. Micaela Matta. 

We are seeking a postdoctoral research associate to contribute to an innovative EU Pathfinder project at the intersection of polymer chemistry, molecular dynamics simulations, and machine learning. The primary goal is to develop an in-silico framework to accelerate the discovery of novel Polyhydroxyalkanoate (PHA) polymers for more sustainable food packaging and to understand their end-of-life degradation mechanisms. The project will be conducted in close collaboration with experimental partners in the project consortium led by AINIA research centre in Spain. 

The postholder will have access to state‑of‑the‑art high‑performance computing (HPC) resources, will be embedded within the Net Zero Centre and the King’s institute for AI, and will work alongside experts in computational and experimental chemistry.

Applicants should have a PhD in Chemistry or a related field, with a strong background in atomistic molecular dynamics simulations of soft mater, especially polymers and/or proteins, and demonstrable experience or strong interest in machine‑learning approaches for accelerating molecular modelling and the prediction of chemical properties.

For informal enquiries, please contact Dr Martin‑Martinez at francisco.martin-martinez@kcl.ac.uk. This post is advertised with an intended start date as soon as possible.

About you

To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

1. A PhD in Chemistry, Physics, Materials Science, or a related discipline.
2. Evidence of the ability to contribute to writing and publishing research papers in peer‑reviewed journals.
3. Proven research background in atomistic molecular dynamics simulations, ideally of polymers and/or proteins, for structure–property prediction and molecular design.
4. Strong experience with python programming for molecular simulation and cheminformatics.
5. Experience with version‑controlled GitHub repositories and Unix/Linux‑based high‑performance computing environments.
6. Good communication skills, including the ability to write scientifically, clearly, and succinctly, and to present research to both specialist and non‑specialist audiences.

Desirable criteria 

1. Experience with machine‑learning interatomic potentials and their deployment in large‑scale molecular dynamics simulations.
2. Experience working in multicultural and international research environments, with a track record of international collaborations.
3. Research experience with modelling molecular and/or materials degradation (e.g., reactive MD, conceptual DFT).
4. Experience with AI/ML for molecular/materials discovery and property prediction. 

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