Overview
Postdoctoral Research Associate – Strand, London, WC2R 2LS
About us
The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research activities and a wide-ranging portfolio of education programmes.
Celebrating diversity and supporting staff is important to us and we offer a range of provision including flexible working, caring support (including a Parenting and Carers Fund and the Carer’s Career Development Fund), training, and a variety of diversity and inclusion networks. Staff can apply for flexible working to help them balance the demands of their professional and personal commitments and we offer comprehensive leave policies for parental, adoption, surrogacy, dependant and shared leave.
The university is making investment in NMES, and both student and staff numbers are growing. Our staff come from over 45 countries and 56% of our students are from outside the UK. Further details available at www.kcl.ac.uk/nms.
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.
IMPORTANT: Before applying for this role, please make sure you have the right to work in the country where the role is based. Unless it clearly stipulates within in the job advert above that the hiring company is looking to or able to sponsor applicants it is deemed that the hiring employer will only consider applications from those able to comply with and work in the country where the role is based.
