Research Fellow (109364-0724)

Duration: 2 years (subject to funding renewal after 12 months)

About the Role  

For informal enquiries, please contact Mona Faraji Niri (Associate Professor) at Mona.faraji-niri@warwick.ac.uk. 

In WMG are undertaking research into how traditional Li ion battery manufacturing processes can be optimised through the application of systems engineering and data science methods. Creating new models and predictive tools to improve battery performance and the underpinning efficiency, repeatability and reliability of the manufacturing process.

We are therefore seeking a Research Fellow to join our team in the NEXTRODE Project Funded by Faraday Institution. You will explore the boundaries of a data-driven approach approaches in which machine learning and deep learning methods are combined with physical models of battery performance to understand if causality exists between manufacturing process variables and key electrode/cell attributes. You will be supporting the academic investigators to coordinate all aspects of the research, including experimental design, data capture, model creation and validation. You will have unique access to the resources of our Energy Innovation Centre (EIC) and bespoke high-performance computing facilities.

The post is funded by the research grant: “Next Generation Electrodes (Nextrode)” that is provided by the Faraday Institution, the UK’s independent institute for electrochemical energy storage research and skills development. The Nextrode consortium comprises a number of leading UK universities including: Warwick, UCL and the universities of Oxford, Sheffield, Birmingham and Southampton. The Faraday Institution vision is to bring together scientists, engineers and industry partners on research projects to reduce battery cost, weight, and volume; to improve performance and reliability (faraday.ac.uk).

The overall aim of the Nextrode project is to seize the emergent opportunity in the manufacture of smart electrodes by investigating: (i) the underlying reasons why current Li ion battery electrode performance in practice falls well short of theory, (ii) novel approaches to electrode design that can overcome these restrictions, and (iii) how these designs can be realized at a scale and cost that makes them attractive to industry. The research encompasses both optimisation of current manufacturing practices based on improved scientific insight, and the development of new electrode manufacturing processes. Across the Nextrode consortium, the research involves elements of design, modelling, manufacture, characterisation and data science.

About You  

You will need a PhD in a relevant discipline, along with excellent computing and program skills in multiple languages and environments. You will also need a problem-solving ability to manage and analyse manufacturing datasets and the ability to publish high-quality academic outputs.

AI/ML and advanced data processing for tabular, time series and image data are required core skills, Battery & manufacturing knowledge are desired.

For further information regarding the skills required for this role please see the personal specification section of the attached job description.

If you are near submission or have recently submitted your PhD but have not yet had it conferred, any offers of employment will be made as Research Assistant at the top of level 5 of the University grade structure. Upon receipt of evidence of the successful award of your PhD, you will be promoted to Research Fellow on the first point of level 6 of the University grade structure. 

Full details of the duties & selection criteria for this role can be found in the vacancy advert on the University of Warwick's jobs pages. You will be routed to this when you click on the Apply button.

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