About the Project
This PhD will run in partnership with the Department of Biology and Soft Robotics. The aim is to develop technological solutions to the growing problem of water scarcity by drawing inspiration from the living world. Plants and animals evolved remarkable strategies to survive drought, from desert beetles that harvest water from fog to plants that reconfigure themselves in response to humidity. These natural systems demonstrate the role of surface structure and form in transforming atmospheric moisture into usable water.
You will translate these biological principles into engineered prototypes. Your goal will be to find new routes to sequestering water by designing adaptive, low-energy devices that operate passively and sustainably. The PhD will combine recent advances in soft robotics, responsive materials and AI-based optimisation merged with biology, bio-derived design rules, and intelligent control to design a new class of adaptive fog-harvesting systems. This will establish new conceptual and technical foundations for nature-based engineering, and advance our understanding of adaptive interfacial phenomena, ultimately yielding reusable tools for biomimetic and sustainable design across energy, architecture, and climate-resilient infrastructure. The candidate can be from a biology or engineering background.
Aims
The aim of this PhD is to develop a new generation of adaptive, low-energy water-harvesting technologies inspired by biological strategies for capturing and managing atmospheric moisture. Working across biology and soft robotics, the student will investigate how organisms, including fog-harvesting insects and humidity-responsive plants, use surface properties, structure, geometry and dynamic changes in form to interact with water. The student will translate these biological principles into bio-inspired design rules and engineered prototypes for passive fog and atmospheric water harvesting. They will explore how responsive materials and soft robotic mechanisms can enable devices to adapt their shape, surface properties or behaviour in response to changing environmental conditions. AI-based optimisation and intelligent control will be used to identify effective designs and improve water-capture performance while minimising energy requirements.
The project ultimately aims to demonstrate adaptive water-harvesting prototypes and establish transferable principles for nature-inspired engineering. In doing so, it will advance understanding of adaptive interfacial phenomena and generate new approaches and design tools with potential applications in sustainable water provision, architecture, energy systems and climate-resilient infrastructure.
Methods
The project will combine biological investigation, microscopy, computational design and engineering. The student will study living plant collections at the Oxford Botanic Garden and biological specimens from the Oxford University Museum of Natural History to identify adaptations associated with water capture and transport. Surface structures and functional features will be characterised using techniques including scanning electron microscopy (SEM) and quantitative imaging. Biological observations will then inform bio-derived design rules, which will be translated into CAD models and fabricated prototypes. These designs will be tested experimentally and iteratively refined using soft robotic approaches, responsive materials and computational optimisation to evaluate and improve water-harvesting performance.
Project code
CT01
Funding
This project is part of the DPhil in Biology programme, and is not a funded course at the University of Oxford; as such, students are expected to explore options for funding. However, we anticipate being able to offer around 6 full graduate scholarships to incoming DPhil students in 2027/28.
You will be automatically considered for several Oxford scholarships, which cover fees and stipend, if you fulfil the eligibility criteria and submit your graduate application by 6 January 2026. Scholarships are awarded based on academic achievement and potential to excel as a DPhil student.
For further details about searching for funding as a graduate student visit the graduate study information on our website.
Eligibility
For full entry requirements and eligibility information, please see the main admissions page.
How to apply
The deadline for applications for 2027/28 entry is 6 January 2027. We will continue to accept applications submitted after this date, but these late applications will not be considered for scholarship funding.
You can find the admissions portal and further information about eligibility and the DPhil in Biology Programme at the University's graduate admissions page. Please quote the Project Reference Code alongside the title in the 'Proposed field and title of research project, if applicable' field in the application form.
Institution website: https://www.biology.ox.ac.uk/dphil
References
Liu, J., Xie, S., Chen, G., et al. (2026). A review on tackling global water scarcity through biomimetic microstructures in fog harvesting devices. Water Research, 126555.
Yao, Y., Howard, D. & Maiolino, P. (2026). Generalized task-driven design of soft robots via reduced-order finite element method-based surrogate modeling. Advanced Intelligent Systems.
Box, F., Erlich, A., Guan, J.H. & Thorogood, C. (2022). Gigantic floating leaves occupy a large surface area at an economical material cost. Science Advances, 8(6), eabg3790.