Biomimetic Engineering Design of Biohybrid Soft Nanorobots to Combat Antimicrobial Resistance and Advance an Integrated Understanding of Illness

Project ID: 2531bd1604

(You will need this ID for your application)

Research Area(s): Antimicrobial resistance
Tackling Infections
Biophysics and soft matter physics

Project Summary:

Bacterial contamination and antimicrobial resistance (AMR) have progressively emerged as alarming public health concerns. For decades, these issues have been primarily addressed through the development and refinement of chemical therapeutics; however, such strategies, largely based on modifying existing compounds, are now approaching their limits in both effectiveness and safety. This PhD project aims to address this challenge through biomimetic engineering design, combining predictive in silico modelling with microfluidic engineering to develop nature-inspired soft-nanorobots. These soft-nanorobots will be built on nanoparticle-stabilised emulsion droplets with responsive capability to mimic macrophage-like engulfment capable of encapsulating and neutralising pathogenic bacteria through a combination of mechanical hindrance and chemical activity. Simultaneously, the research will initiate the development of a biomimicry-based framework with public health practitioners, community members and those with lived experience to promote a new understanding of biomimicry as a design principle to support engagement and implementation of the technology for future practice. Overall, these activities will contribute to advancing the design of technologies and frameworks that incorporate scientific, clinical, and community perspectives, fostering a more comprehensive understanding of illness and AMR.

This project combines machine-learning-augmented simulations and microfluidic engineering to explore the biomimetic design of antimicrobial nanotechnology. The engineering design will be supported with practice-based research to develop new ontological thinking and knowledge creation processes through integrating engineering and public health disciplines.

You will be hosted at UCL Arts & Sciences and collaborate with UCL Chemical Engineering and work closely with experts in in-silico engineering and applied machine-learning (Dr Francois Sicard), complex multiphase flows (Prof Panagiota Angeli), and pharmacy practice (Dr Ranjita Dhital).

You have a postgraduate degree in natural sciences (e.g., Physics, Chemistry) with an interest in interdisciplinary research in machine-learning-augmented computer simulations and experimental chemical engineering and are motivated by implementing sciences and practices related to public health impact of healthcare nanotechnologies.