Circulating tumour cells (CTCs) are cancer cells that detach from primary or metastatic tumours and enter the bloodstream, offering a rich source of information for early detection, monitoring of disease progression, and tailoring personalised treatments. However, isolating these cells remains extremely difficult. They are exceptionally rare, and their physical properties—such as size, shape, and deformability—vary widely across patients, cancer types and disease stages. Most existing microfluidic separation devices struggle because they are optimised for a narrow range of cell characteristics and cannot accommodate this biological variability. Inertial microfluidics is a rapidly growing technology that uses hydrodynamic forces to focus and separate cells at high throughput without the need for chemical labels. While powerful, current devices share one fundamental limitation: their internal flow environment is fixed once fabricated. As a result, they cannot be tuned or adapted to different sample conditions. A device that performs well for one patient or cancer type may perform poorly for another. This PhD project aims to address this challenge by developing adaptive inertial microfluidic systems—devices in which the internal flow behaviour can be modified or controlled after fabrication. Rather than relying on static geometries or single-purpose designs, the project will explore approaches that allow the microscale flow field to respond to changes in operating conditions, making it possible to tailor separation performance to unknown or variable CTC properties. This shift from static to adaptive design has the potential to yield more universal diagnostic platforms capable of handling diverse clinical samples without prior knowledge of cancer type or stage. The project will integrate advanced computational modelling with experimental microfluidics. Computationally, the student will use high-fidelity simulations to investigate how inertial flow structures change under adaptive conditions and how these changes influence particle and cell migration. Numerical modelling provides complete spatial and temporal datasets, enabling the exploration of underlying physical mechanisms that cannot be directly observed in the laboratory.

 Experimentally, the student will fabricate and test prototype devices, characterising flow behaviour and cell analog trajectories to validate and refine the computational findings. This combined approach ensures both deep physical insight and practical relevance. The supervisory team provides strong complementary expertise: Dr Sally Peyman (Heriot-Watt University) – experimental microfluidics, device development, biomedical applications Dr Benjamin Owen (University of Edinburgh) – computational modelling, multiphysics simulation, inertial microfluidic theory The project also benefits from collaboration with Prof. Ian Papautsky (University of Illinois Chicago), a world-leading figure in microfluidic cancer diagnostics and Director of CADMIM. His involvement provides industry-informed guidance on translation and real-world applicability. This PhD offers an exciting opportunity to work at the intersection of biomedical engineering, fluid dynamics, and microsystem design. The student will gain expertise in high-performance computing, fluid simulation, microfabrication, microscopy and diagnostic technology development. The outcomes of this project have the potential to significantly advance patient-specific liquid biopsy tools and contribute to the next generation of adaptive lab-on-chip systems.

Minimum entry qualification- an Honours degree at 2:1 or above (or international equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree

Further information on English language requirements for EU/Overseas applicants.

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.

Competition (EPSRC) funding may be available for an exceptional candidate but please note you must be a UK student or an EU student who has pre-settled/settled status and has lived in the UK for at least 3 years.

Further information and other funding options.