University of Exeter invites applications for a doctoral studentship focused on multiscale scientific machine learning for predicting thermal trajectories, torque capability and efficiency in low-speed, high-torque propulsion systems. The project blends physics-informed neural networks, recurrent models and Neural ODEs, with digital-twin validation and experimental data from a high-performance dynamometer.
You will collaborate with Ecomar Innovations on industrial hardware, spend significant
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Multiscale SciML Digital Twin for High-Torque Propulsion in Exeter employer: University of Exeter
The University of Exeter is an exceptional employer, offering a supportive and inclusive work environment that prioritises employee wellbeing and professional growth. With flexible working opportunities, generous annual leave, and a commitment to diversity and social justice, staff can thrive while contributing to meaningful initiatives that enhance student employability. Located in Exeter, this role provides a unique chance to engage with a diverse community and make a tangible impact on the future of underrepresented students.
