Research Fellow in Modelling Solid-state Batteries

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The role

Applications are invited for a Research Fellow position in Modelling Solid-state Batteries. The Research Fellow will work within a big consortium OPERA - A Horizon Europe Project (horizon-opera.eu) and will collaborate with leading experimental scientists from Spain, Germany, Norway, Austria, France, and Slovekia, who will develop zero-excess solid-state Li/Na-ion batteries, and operando techniques to understand the anode-electrolyte interfaces. The candidate will also have opportunities to interact with wider EU battery communities through the engagement with BATTERY 2030+ large scale initiative on Future Battery Technologies and collaboration. 

The post will be based within the School of Chemistry and Chemical Engineering (SCCE) at the University of Surrey, and will have opportunity to interact with a vibrant Sustainable Energy and Materials research team and the Digital Chemical Engineering team with 20 academics and more than 50 PhD and postdoc researchers. The Sustainable Energy and Materials team at the University of Surrey has a strong background in the design, synthesis, optimisation and application of advanced functional materials for energy conversion and storage. The research group has specific interests in multiscale materials modelling combined with experimental approaches for a variety of sustainable electrochemical technologies including fuel cells, electrolysers, and batteries. 

The University of Surrey is ranked 13th in the UK in the recent Complete University Guide, and was awarded The University of the Year for Graduate Employment in 2021. You will be well supported for your career development with comprehensive tailor-designed training programme for researchers, mentoring schemes, and one-to-one career advice and support.

About you

We invite researchers with experience in computational modelling and/or AI to apply. If you have worked with computational modelling using any of the following methods: finite volume/CFD, finite element/COMSOL Multiphysics, phase-field theory, lattice Boltzmann, then you will be suited for this project. Within the project, you will carry out meso-scale simulations of Li/Na dendrite growth and mechanical stress-strain behaviour of materials in solid-state batteries; you will also have opportunities to learn and use machine learning methods to assist multiscale modelling for zero-excess solid-state batteries. Experience in batteries and electrochemical energy technologies are desirable but not essential.

The appointed candidate will collaborate with two Research Fellows who work on atomistic modelling, as well as other Research Fellows and PhD students in Prof Qiong Cai’s group who work on mesoscale materials modelling for electrochemical energy devices. The appointed candidate will also collaborate with researchers in Prof Tao Chen’s group for using machine learning methods. 

Candidates must hold (or be close to completion of) a PhD in Chemical Engineering, Mechanical Engineering, Material Science, Physics or other relevant major degrees.  

Apply online, carefully answer all the application form questions, and attach a curriculum vitae (with details on education, research experiences, successes and the relevant publications to date). 

How to apply

Prospective applicants can contact Prof Qiong Cai ([email protected] ) and Prof Tao Chen ([email protected] ), if they need any specific further information on the post.