[School of Engineering PhD Scholarships] From Nature to Mechanism: Inverse Design of Soft Robot via Differentiable Rendering Base Self-Modeling

About the project

About the Project This PhD project investigates biomimicry-inspired kinematics and inverse design for soft robots by integrating differentiable simulation, Gaussian splatting-based differentiable rendering, and self-modeling. Building on the existing differentiable soft-robot simulation framework developed in the Digital Manufacturing Lab at the University of Manchester, the research aims to translate complex biological motion and deformation into realizable robotic designs. Motion and deformation data from animals will be collected and reconstructed using Gaussian splatting, providing differentiable 3D representations of natural movement. These representations will be coupled with differentiable soft-body simulation to optimize robot morphology, material properties, and actuation through gradient-based methods. The resulting self-modeling framework will allow soft robots to refine their internal models from visual observations and reduce discrepancies between simulated and real-world behaviour. The project will establish an inverse-design pipeline from biological motion to robotic mechanism, enabling soft robots to reproduce adaptive movement patterns observed in nature while reducing reliance on manual trial-and-error design. Experimental validation using fabricated soft robotic prototypes will assess the accuracy, adaptability, and physical transferability of the proposed approach. Expected outcomes include a Gaussian splatting-based differentiable self-modeling framework, new methods for bio-inspired inverse design, and improved strategies for jointly optimizing soft-robot morphology and behaviour. Potential applications include medical robotics, environmental exploration, adaptive manipulation, and locomotion in complex environments. This project is expected to start in September 2027. Before you apply: We strongly recommend that you contact the supervisors for this project before you apply. How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Engineering Scholarships . If you don’t already have an applicant account, please follow the instructions here. . When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing the motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications . Please note late or incomplete applications will not be considered. Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status. We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder. Eligibility : The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in a discipline directly relevant to the PhD (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD (or international equivalent). Applicants are preferred to have a background in computational design, digital manufacturing or robotics; excellent skills in mathematics and programming (C++/Python and geometric computing) are preferred. This project will remain open until filled. If your application is submitted by 1 st November 2026, you can expect a decision by 18 th December 2026. If your application is submitted by 15 th January 2027, you can expect a decision by 30 th March 2027. Self or externally funded students can also be considered for this project. FSESoE

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