At Materials Nexus, we care passionately about the future of our planet and are determined to make the world a better place for generations to come. For us, this means discovering new genuinely green materials with improved performance and reduced environmental impact.

We do this by harnessing the power of machine learning and quantum mechanics. We are building a revolutionary new material discovery platform that can vastly accelerate the development of new materials compared with traditional experimental approaches.

We are looking to expand our technical team with a computational thermodynamicist to play a major role in expanding our thermodynamic modelling and simulation capabilities, to help bridge the gap between computation and experiment. The role will involve the implementation of thermodynamic techniques such as CALPHAD, CEF, CFD, and phase-field for the modelling of novel materials in a high-throughput environment. Since experimental data is not available for novel materials, modelling will be supported by ab initio methods such as density functional theory.

The ideal candidate for this role would be a computational scientist keen to build impactful tools for materials science leading directly to environmental benefits, with well-developed abilities in thermodynamics.

For more information, and to apply, please visit our website: https://www.materialsnexus.com/jobs/computational-thermodynamicist