Research Assistant in Motor-twin Development and Validation

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We are inviting applications for a Research Assistant to support the University of Sheffield's contribution to the SMART (Secure Motor AI-Responsive Technology) project. The post will contribute to the development and validation of computationally efficient motor-twin models for permanent magnet synchronous machines. The work will focus on machine modelling, parameter and state estimation, plus preparing modelling outputs that can be shared with project's partners.

The successful candidate will work with academic and industrial project partners to generate simulation and experimental validation evidence, using available machine data, dynamometer testing, and HIL methods. The role will also involve documenting methods and results for project deliverables, reports and publications.

The post is suited to candidates with a PhD awarded or close to completion (or equivalent experience), in electrical machines, drives, control, real-time simulation, or a closely related engineering discipline, who is motivated to develop deployable motor-twin methods for intelligent motor drives.

The post is for the duration of 2 months and for a maximum of 20 hours per week.

• Develop and implement motor-twin models for BLDC/PMSM drives, including parameters and state estimation.
• Deliver reduced-order high-fidelity electrical machine modelling methods suitable for simulation, HIL and real-time controller.
• Support validation using HIL platforms, dynamometer testing and environmental characterisation data, as required by the project plan.
• Work collaboratively with academic and industrial project partners, present progress, and maintain clear technical records, code, data and documentation. Contribute to project deliverables for the University of Sheffield work package.
• Contribute to dissemination activities, including preparation of technical reports, conference or journal papers.
• Carry out other duties, commensurate with the grade and remit of the post.

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.

• A PhD or working towards a PhD degree in electrical engineering (or equivalent experience) — Essential — Application
• Experience in modelling, simulation or analysis of electrical machines or electric drives, such as BLDC/PMSM systems — Essential — Application/interview
• Experience using engineering software or programming tools for modelling and data analysis, such as MATLAB/Simulink, Python, finite-element tools or equivalent — Essential — Application/Interview
• Awareness/knowledge of field-oriented control, FPGA-based control, GaN inverter technologies, or adaptive-control concepts — Desirable — Application
• Good written and verbal communication skills, including experience writing reports and presenting your findings — Essential — Application/interview
• Ability to work effectively within a team environment — Essential — Application/interview
• Ability to plan own workload and prioritise conflicting deadlines — Essential — Application/interview
• Effective time management skills — Essential — Application/interview
• Ability to plan research tasks and progress work activities, and to monitor and manage the delivery of outcomes —…