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3D nanoprinted cell scaffolds for oxygen and pH sensing

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  • Full or part time
    Dr N Radacsi
    Dr S Smith
    Prof I Underwood
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Fully funded PhD studentship available on 3D optically responsive nanostructured cell scaffolds. This is a 4-year PhD (unlike the standard 3.5 year UK PhD), as it is within the EPSRC Centre for Doctoral Training in Intelligent Sensing and Measurement. You will learn how to synthesize and characterize optical nanostructures for monitoring clinically relevant bio-markers, how to fabricate 3D nanostructures (3D nanoprinting), how to integrate optical probes within cell scaffolds, how to assess in vitro sensor performance and how to work with cell cultures. Within the project you will use state-of-the-art characterization techniques. Part of the work will be carried out at the material research institute Empa in St. Gallen (Switzerland) (ETH domain). You will work with our prototype 3D nanoprinter, make solutions and hydrogels, use cell cultures and microscopes (SEM, confocal, fluorescent, etc.)

Experience with cell cultures and/or nanotechnology is required.

Self-funded candidates from all over the world are also encouraged to apply.

Research group website:

Funding Notes

Minimum entry qualification – a First Class degree (or International equivalent) in materials science, chemical engineering or physics discipline, possibly supported by an MSc degree. Experience in nanotechnology and their characterization techniques is a plus, but not essential. Experience with CAD software is essential.

EPSRC funded. Tuition fees and stipend available for Home students or EU students who have been resident in the UK for 3 years (applications also welcome from self-funded international students).

How good is research at University of Edinburgh in General Engineering?
(joint submission with Heriot-Watt University)

FTE Category A staff submitted: 91.80

Research output data provided by the Research Excellence Framework (REF)

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