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Inertial microfluidics modelling for particle separation and disease diagnostics

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  • Full or part time
    Dr T Krueger
    Dr S Smith
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

With antimicrobial resistance and cancer becoming more demanding challenges worldwide, new diagnostic tools are required in order to detect bacteria or circulating tumour cells in blood samples. Microfluidics has become an established technology for the processing of blood samples with volumes between micro- and millilitres. One emerging microfluidic technology is inertial microfluidics (IMF), promising larger throughput and more accurate cell separation than other methods. IMF is still not well understood, which limits its current applicability.

We are currently looking for an ambitious and motivated researcher at the PhD student level to explore IMF. The successful PhD candidate will develop numerical models, perform computer simulations, and analyse the particle and fluid dynamics of IMF in order to uncover the underlying physics and enabling engineering applications. Publishing research papers and presenting results at international conferences will be expected of the PhD student.

The PhD project is aligned with Dr Krüger’s ERC Starting Grant “SIRIUS” (https://cordis.europa.eu/project/rcn/217970/factsheet/en). The PhD candidate will work in an interdisciplinary Edinburgh-based group with engineers, physicists and biologists. The group has a number of ongoing international collaborations on microfluidic modelling and their applications. The successful candidate will have the freedom to define her/his own project in the context of “SIRIUS”.

Eligibility:
A strong academic track record with a 2:1 or higher in a relevant undergraduate degree (e.g. Chemical or Mechanical Engineering, Physics, Mathematics), or its equivalent if outside the UK. A strong performance in a relevant postgraduate degree is desirable. Proven experience in one or more of the following is desirable: mathematical modelling, computational fluid dynamics, competence in one scientific programming language (e.g. C++, Python, Fortran).

Further information:
www.timm-krueger.de

Funding Notes

Tuition fees + stipend are available for Home/EU students (International students can apply, but the funding only covers the Home/EU fee rate).

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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