Generative Computer-Assisted Design (GeCAD) of Biohybrid Soft Nanorobots for Targeted Bacterial Pathogen Capture

Project ID: 2228cd1353 (You will need this ID for your application)

Project Summary:

Bacterial contamination and antimicrobial resistance (AMR) have progressively emerged as alarming public health issues. As nanotechnologies have become a promising alternative to traditional antibiotics for overcoming AMR, their design has yet to meaningfully engage community participants, health practitioners and those with lived experience, essential for the adoption and scale of health innovations. This is particularly relevant at the early-stage design where the potential value of such an approach remains unknown. This interdisciplinary project explores the computer-assisted design of antibacterial soft-nanorobot technologies and their social and ethical implications on patient care and clinical practice. It also explores the potential of a participatory, co-constructed approach to design for our integrated understanding of illness and AMR.

This project combines predictive computational modelling and research-based practice to explore the co-creation of antimicrobial nanotechnology that remains close to experimental conditions and meaningfully engages with those with lived experience and clinical practice. You will learn and exploit advanced computational approaches, including molecular dynamics simulations and machine learning to advance the design of nanoparticle-stabilized emulsion droplets with responsive capability for bacteria capture in the condition of spray-related medication. The computer-assisted design will be supported with practice-based research, including multi-modal methodologies, such as creative narrative interviews, to generate a diverse range and depth of health and social implications which could enhance nanotechnology. This participatory study not only seeks to ensure that the early-stage design of the technology is relevant to end-users with lived experience but also paves the way for a generative co-design framework for the computational stage of healthcare innovation.

You will be part of UCL Arts & Sciences and work closely with experts in responsive nanomaterials, public health, social research and pharmacy practice.

You will have a postgraduate degree in natural or social science with an interest in interdisciplinary research in engineering, computational and social sciences.