PhD in Adaptive Inertial Microfluidics for Cancer Cell Separation (Computational Modelling & Experimental Microfluidics)

A PhD studentship is available in the field of adaptive inertial microfluidics for universal cancer cell separation, jointly supervised by Associate Professor Sally A. Peyman (Heriot-Watt University) and Dr Benjamin Owen (University of Edinburgh). The project focuses on developing advanced microfluidic systems capable of separating circulating tumour cells (CTCs) from blood, which is crucial for early cancer detection, monitoring disease progression, and personalizing treatments. The research addresses the challenge of isolating rare CTCs with diverse physical properties by designing adaptive microfluidic devices whose internal flow environments can be tuned post-fabrication, enabling universal application across different cancer types and patient samples. The student will integrate computational modelling and experimental microfluidics, using high-fidelity simulations to study inertial flow structures and their impact on cell migration, and fabricating/testing prototype devices to validate computational findings. The project offers training in high-performance computing, fluid simulation, microfabrication, microscopy, and diagnostic technology development. Collaboration with Prof. Ian Papautsky (University of Illinois Chicago) adds industry-informed guidance and real-world applicability. Applicants should hold at least a 2:1 Honours degree (or international equivalent) in a relevant science or engineering discipline, with an MSc degree desirable. English language requirements apply for EU/Overseas applicants. EPSRC competition funding may be available for UK residents or EU students with pre-settled/settled status and at least 3 years UK residency; otherwise, students must be self-funded or secure scholarships. The closing date for applications is 9 January 2026. For more information and to apply, visit the University of Edinburgh's website or contact Dr Benjamin Owen. This opportunity is ideal for candidates interested in biomedical engineering, fluid dynamics, computational modelling, and lab-on-chip diagnostics.