Research Assistant in Materials Modelling

Job id: 159665 . Salary: £39,076 - £43,909 per annum, including London Weighting Allowance .

Posted: 19 October 2026 . Closing date: 02 November 2026 .

Business unit: Natural, Mathematical & Engineering Sci . Department: Physics .

Contact details: Chiara Gattinoni . chiara.gattinoni@kcl.ac.uk

Location: Strand Campus . Category: Research .

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About us

The available postdoctoral associate position is based in the Physics Department at King’s College London, one of the UK’s best Physics Departments with the QS World University Rankings placing us in the top 10 universities in the country.

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.

About the role

Applications are invited for a postdoctoral position in the group of Dr. Chiara Gattinoni — within the Theory and Simulation of Condensed Matter research group — on the materials modelling of ultrathin ferroelectric films. The overall goal of this research project is to produce strategies to manipulate the polarization in ultrathin ferroelectrics, and to design ferroelectric thin films possessing the desired magnitude and direction of the polarization.

The successful candidate will develop machine learned interatomic potentials for the study of ultrathin ferroelectric films.

This position is supported by the EPSRC New Investigator Award grant “Customisable polarization in ultrathin ferroelectrics”.

The position is based in the Department of Physics, King’s College London on the Strand Campus in the heart of central London.

This is a full-time post (35 Hours per week), and you will be offered a fixed term contract with a 6 months length.

About you

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

Essential criteria

• BSc in Physics, Materials Science of related subject

• PhD in Materials modelling, computational physics or related subject (either complete or close to completion)

• Excellent skills in programming and data analysis

• Experience of atomistic simulation techniques

• Ability to work independently and as part of a team

• Excellent communication skills

Desirable criteria

• Experience of atomistic modelling of ferroelectric materials

• Experience in development and application of machine learned potentials

Downloading a copy of our Job Description

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process.

Further Information

At King’s, we believe that the diversity of our community and a culture that is welcoming, open, inclusive and collaborative, are great strengths of the university.

The Equality Act of 2010 protects the rights of our students and staff and provides a framework to fulfil our duties to eliminate unlawful discrimination, harassment and victimisation and in addition, to advance equality of opportunity and foster good relations between those who share a protected characteristic and those who do not. At times, this will include balancing rights and beliefs that can feel in tension.

We are committed to free speech and to academic freedom, believing that our foundational purpose as a university, is to create spaces where a wide range of ideas, including ideas that are controversial, can be discussed and debated, and where members of our community can express lawful views without fear of intimidation, harassment or discrimination.

When engaging in the robust exchange of ideas, we ask that our community is mindful of our Dignity at King’s guidance.

We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the person specification section of the job description. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

Artificial intelligence (AI) is evolving rapidly, and we recognise its growing role in professional work. Applicants may use AI tools to support preparation of their application, for example to research the role or structure written responses. However, applications must reflect the applicant’s own work and experience. AI tools should not be used during interviews or assessment activities unless this has been agreed in advance as a reasonable adjustment. Further guidance on the use of AI in recruitment can be found here .

We reserve the right to close adverts early due to the volume of applications we receive. While the closing date may change, all adverts will close at 23:59 to allow sufficient time for applications to be submitted on that day.

We encourage you to apply at the earliest opportunity to avoid disappointment as once we have closed a vacancy you will be unable to submit your application.

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