Computational Materials Scientist

About the Opportunity

We are seeking a Computational Materials Scientist to join our Advanced Systems & Consultancy Sub Division of our Technology Division. We have a growing team of materials modellers and are looking for someone to join this high performing group, who can help us reach our goals of becoming a world leading research centre.

This role focuses on the development of mechanistically informed models to predict degradation behaviour in materials. The role requires a preexisting knowledge and skill set in one or more of the following modelling methods: molecular dynamics, density functional theory, kinetic rate theory, CALPHAD or machine learning. The role will utilise these skills to model the behaviour and degradation of reactor core materials, particularly cladding and fuel, and their performance under in reactor conditions.

You will join the Structural Integrity and Materials Engineering (SIME) team, with opportunities to collaborate across other teams and broaden your expertise in modelling methods.

Key Responsibilities

• Design and implement atomistic simulations to support mechanistic understanding of materials in extreme environments.
• Support the development of modelling programmes and emergent modelling techniques.
• Analyse data and prepare technical reports to deadlines.
• Collaborate with the experimental teams to inform predictive models.
• Write and review technical reports to deadlines.
• Interface with external stakeholders and contribute to multipartite research programmes.
• Build links with academic institutes and actively scope new research projects.

Here's What You'll Need

• PhD (or near completion) in materials science, mathematical modelling, computational chemistry or a related discipline.
• A preexisting knowledge and experience with one or more of the following modelling methods: molecular dynamics (e.g. LAMMPS, GROMACS), density functional theory (VASP, Quantum ESPRESSO), kinetic rate theory, CALPHAD (Thermo Calc) or machine learning frameworks/tools.
• Basic proficiency in Python for scientific computing and data analysis.
• Solid foundation in handling and analysing large data sets.
• Ability to work collaboratively in a scientific environment.

Work-Life Balance

Work life balance and flexibility is a key focus area for us. We're happy to discuss hybrid, part time and flexible working hours, patterns and locations to suit you and our business.

We partner with VERCIDA, for greater online accessibility please visit to view and access our roles. As a Disability Confident employer, we will interview all disabled applicants who meet the minimum criteria for a vacancy. We welcome applications from candidates who are seeking flexible working and from those who may not meet all the listed requirements for a role.

If you require further support or reasonable adjustments with regards to the recruitment process (for example, you require the application form in a different format), please contact the team.