University of Bath LURS Studentship: Modelling and Design of Dexterous Soft Robotic Manipulators

University of Bath

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The Department of Mechanical Engineering at the University of Bath is inviting applications for the following fully-funded PhD project.

This advert will close when a suitable candidate is identified. Early application is therefore encouraged.

Project Description

Applications are invited for a PhD position to play a pivotal role in the modelling and design of soft robotic manipulators, contributing to our ambitious project of developing a new analytical framework for dexterous robotic systems. This role is funded by ARIA (Advanced Research and Invention Agency), and the successful applicant will be based at the University of Bath. The emerging technology of soft robotics exploits flexible and compliant materials for their design. They are able to translate fundamental biological principles into new engineering design rules or combine life-like components into a synthetic structure to create robotic systems that perform very much like a natural system. Soft robotic systems provide a route to increase body flexibility, improve dexterous handling in unstructured environments, enable adaptability of wearable and medical devices, and safer human-machine interaction. Machine Learning (ML) is an emerging technology with significant potential in integrating and embodying soft robotics technologies, but it is in its infancy in this area. This high-risk, high-gain project will provide a step-change and lead to advances at the frontiers of knowledge in soft robotics by creating a new analytical modelling framework which involves new model- and learning-based approaches and their integration to allow modelling, prediction, control and understanding of soft robotic manipulators. The role will be focused on the development of high-fidelity physics-based models to fundamentally understand soft-body mechanics and the relations between the actuation space and the deformation of the soft manipulator body. The new framework will address and overcome “frustrating unpredictability”, “surprising results”, “ineffectiveness and inaccuracy”, and “unreliability” of the soft manipulators during motion, as well as “a lack of understanding and tools” challenge during research on soft robotics.

Applicant Requirements

Candidates with experience/interest in soft robotics, control engineering, dynamic systems, modelling and simulation are welcome to apply. Applicants should hold, or expect to receive, a First Class or good Upper Second Class Honours degree (or the equivalent). A master’s level qualification would also be advantageous. Non-UK applicants must meet our English language entry requirement.

https://www.bath.ac.uk/corporate-information/postgraduate-research-degrees-english-language-requirements-for-international-students/

Enquiries and Applications

Informal enquiries are welcomed and should be directed to Prof Min Pan –

Formal applications should be made via the University of Bath’s online application form for a PhD in Mechanical Engineering.

You must select ‘University of Bath LURS’ from the dropdown menu in the ‘Funding your studies’ section of the application form and provide the supervisor’s name and project title in the ‘Your PhD project’ section. Failure to complete these steps will result in a delay to the processing of your application and may cause you to miss the deadline.

More information about applying for a PhD at Bath may be found on our website.

Equality, Diversity and Inclusion

We value a diverse research environment and aim to be an inclusive university, where difference is celebrated and respected. We welcome and encourage applications from under-represented groups.

If you have circumstances that you feel we should be aware of that have affected your educational attainment, then please feel free to tell us about it in your application form. The best way to do this is a short paragraph at the end of your personal statement.

Project Keywords: soft robotics, robotics, control engineering, dynamic systems, modelling and simulation

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