Research Fellow

Salary: Full time starting salary is normally in the range £34,980 to £44,263 with potential progression once in post to £46,974

Contract Type: Fixed Term contract up to December 2026

Role Summary

Based in the School of Metallurgy and Materials, an exciting Research Fellow position is available in the field of materials discovery and computational modelling of materials, with a focus on developing computational methods to formulate new High Entropy Alloys, joining the project ‘M2DESCO, funded by the EU Horizon. The postholder will work within Dr Beñat Gurrutxaga-Lerma’s research group:

https://www.birmingham.ac.uk/staff/profiles/metallurgy/gurrutxaga-lema-benat.aspx

Joining with our partners at PoliTo and IMR, the project will combine several state-of-the-art materials modelling techniques (DFT, ML, MD, CALPHAD) to develop a new modelling hierarchy with which to predict stable HEAs. This ambitious project will establish a new modelling paradigm for HEAs, rooted in the atomistic prediction of stable compositions and phase structures using Materials Discovery frameworks, followed by the development of novel machine-learning interatomic potentials for the most promising HEA formulations. These will then be employed to predict relevant properties such as mechanical properties of the target HEAs and offer a ranking of formulations to help guide our experimental partners in the development of new HEA coatings.

The role will focus on the development of a computational hierarchy with which to discover new HEA formulations that avoid critical and rare elements. This post-holder will rely on using Density Functional Theory (DFT) for ab initio modelling to predict stable phases and crystal structures. The post-holder will use the DFT predictions to develop a large dataset with different configurations for some HEA case studies to train Machine-Learning interatomic force fields based. The postholder will develop the computational tools, and interface them with software packages such as VASP, Castep and LAMMPS. As this will be a key aspect of the role, experience in code development (Python, C++, Fortran) and/or numerical analysis will be beneficial. Prior experience with density functional theory, molecular dynamics, machine learning or materials discovery methods will also be advantageous.

The postholder will work closely with the project partners to link simulation tools to experimental data and support the research group, including supervision of students.

Person Specification

• Hold, or be close to completion of, a PhD relevant to research area or equivalent experience/ qualifications.
• Experience/Interest in computational modelling.
• Experience in computer programming and code development (e.g. Python, C++) will be advantageous.

Informal enquires can be made to Dr Beñat Gurrutxaga-Lerma, b.gurrutxagalerma.1@bham.ac.uk.

To download the full job description and details of this position and submit an electronic application online please click on the above ‘Apply’ button.

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