Bioengineering

Soft Systems Group website

• BEng(hons), MRes, PhD

• Member of the Royal Society of Edinburgh Young Academy of Scotland (MYAS)

• Programme Director: MSc Electronics

Professor Guangzhao Mao

Head of the School of Engineering | Chair Professor of Materials Engineering

Professor Guangzhao Mao is a leading innovator in nanotechnology and materials engineering, shaping the future of nanomedicine and advanced sensor systems. As Head of the School of Engineering at the University of Edinburgh, she spearheads cutting-edge research that bridges engineering and medicine, unlocking groundbreaking possibilities in drug delivery and nanoscale material applications.

Her pioneering research focuses on two transformative areas:

Electrocrystallization & Nanosensors. Her research unravels the fundamental processes of nucleation and crystal growth in electrodeposition, applying these insights to develop next-generation gas sensors. Her work enhances sensor scalability, with impactful applications in medical diagnostics, environmental monitoring, and industrial automation. Her breakthroughs in integrating nanosensors into larger systems are redefining their real-world potential.

Nanotechnology & Neuroscience. Merging nanotechnology with neuroscience, Mao’s team is developing revolutionary drug delivery systems targeting the central nervous system. Her protein-drug nanoconjugates offer a novel way to bypass the blood-brain barrier (BBB), a long-standing challenge in treating neurological disorders. This innovative approach has already shown promising results in enhancing respiratory function for spinal cord injury, with significant implications for neurodegenerative disease treatments. Her latest advancements include a microfluidic cell-based assay that accelerates drug screening and preclinical evaluations.

Global Recognition & Leadership

Before joining the University of Edinburgh, Professor Mao led as Head of the School of Chemical Engineering at UNSW Sydney, where she continues as an Adjunct Professor. Her global influence is reflected in prestigious accolades, including:✔ Fulbright Senior Scholarship✔ Visiting Professorship at the Max Planck Institute of Colloids and Interfaces✔ Fellow of the American Institute of Chemical Engineers (AIChE)✔ Career Award from the U.S. National Science Foundation

With an impressive track record of driving scientific innovation, Professor Mao continues to push the boundaries of chemical & materials engineering, shaping the next generation of engineering solutions with real-world impact.

B.Sc., Ph.D.

Alan Murray is Professor of Neural Electronics and Assistant Principal, Academic Support. He introduced the Pulse Stream method for analogue neural VLSI in 1985. Alan’s interests are now primarily in implanted silicon chips for biomedical applications.

He led the £5.2M IMPACT (Implantable Microsystems for Personalised And-Cancer Treatment) project, funded by an EPSRC Programme Grant and enjoys teaching first year engineering/electronics and third year Electromagnetics courses. IMPACT produced proof-of-concept results that will be taken forward in two areas – cancer and wound-healing, as "OPTIMIST" (Optimised, Personalised Treatment & Intervention: Microsystems, Implanted Sensors & Therapeutics).

Alan is a Fellow of IET, IEEE and the Royal Society of Edinburgh, Principal Fellow of the HEA and has published over 360 academic papers. Alan’s degrees are in Physics (BSc and PhD – both from the University of Edinburgh). Subsequently, he has done this...

• 1978-80: Research Fellow, Solid – State Physics, Chalk River Nuclear Laboratories: supported by SERC NATO and Canadian NERC fellowships
• 1980-81: Research Fellow, Department of Physics, University of Edinburgh, leading the Light Scattering section of the Condensed Matter group
• 1981-84: VLSI Designer, Wolfson Microelectronics Institute
• 1984-91: Lecturer, Department of Electrical Engineering
• 1991-94: Reader, Department of Electrical Engineering
• 1994-present: Professor of Neural Electronics
• 2002-2008: Head of the Institute for Integrated Micro and Nano Systems
• 2008-2012: Head of the School of Engineering
• 2012-2015: Dean of Students, College of Science and Engineering
• 2015-2018: Head of the Institute for BioEngineering
• 2015-present: Assistant Principal, Academic Support

• B.Sc. Ph.D

• F.I.E.E., F.I.E.E.E., F.R.S.E., C.Eng., P.F.H.E.A.

• Fundamentals of Electronics, Electromagnetism,

• Outside interests : Music (especially folk music - writing, playing and listening) and wood-carving

Electrosynbionics [1] involves the use of biological parts to create devices that generate electricity, such as biological photovoltaics and biobatteries. Electrosynbionic systems can be sustainable power sources for electronics, supporting the Green Transition.

Biosensing involves detection of biological targets, often for diagnosing or monitoring disease. Cheap and effective biosensors can save lives.

Biomimetic membranes can be vital components of electrosynbionic or biosensing devices. For maximizing performance, we need to use sophisticated nature-inspired membranes that are folded or crinkled. The PhD student will investigate different biomimetic materials and explore how to build membranes with complicated morphologies that will deliver optimal performance in devices.

The project will begin with a literature review. This will be coupled to a technoeconomic analysis of biomimetic membranes, the aim of which will be to assess suitability of different materials for applications involving mass production. For training purposes, the student will reproduce selected literature results before moving on to systems of their own design. They will design, build and characterise complex membrane structures, demonstrating the ability to engineer the membrane shape. They will test the effect of using their structures in selected devices.

The student will be trained in wet lab techniques and advanced characterisation methods. Subject to student eligibility and availability of opportunities, they will be able to teach, engage in public outreach or explore other opportunities complementary to their research. They will be encouraged to engage with appropriate University training, as well as to participate in the intellectual community provided by the School of Engineering’s Institute for Bioengineering, in which they will be based.

As this project will complement other research with commercial applications and/or industrial partners, the student will be required to assign intellectual property arising from their PhD to the university, as a condition of accepting the offer. The PhD is fully-funded for Home Students/EU students, with a budget for research consumables. 

[1] Dunn, K.E. The emerging science of electrosynbionics Bioinspiration & biomimetics (2020) DOI: 10.1088/1748-3190/ab654f

https://www.katherinedunnresearch.eng.ed.ac.uk/

A 2:1 undergraduate degree (or equivalent) in a relevant subject e.g. biological sciences, bioengineering, biophysics, materials science. 

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

Tuition fees + stipend are available for applicants who qualify as Home/EU applicants.

Further information and other funding options.

Research Theme

Sensor Signal Processing

Autonomous Sensing Platforms

Aim

Build a smart garment sensor that spots heat strain on the body in real time, using very low power (about one-thousandth of a watt) and reaching high accuracy (around 90%) in realistic military settings.

Objectives

1. Build a garment-mounted panel measuring sweat rate, electrolytes (sodium/chloride or bulk conductivity), sweat lactate, and skin temperature.
2. Implement edge artificial intelligence (Tiny Machine Learning) to deliver continuous on-body inference at ≤1 mW average power.
3. Validate in controlled heat/exertion trials, demonstrating ≥90% event-detection F1 and robust operation under sweat and movement.
4. Quantify inter-subject variability (sex, BMI, fitness/acclimation) and perform a 5–10 min per-user calibration (offset/scale or few-shot adaptation); report within- and cross-subject performance.
5. Exposure add-on: Include a chemical-exposure co-monitor (oxidants/irritants) with event qualification (duration–intensity product; recovery slope), targeting F1 ≥0.85 at ≤1 mW incremental power.

Description

We will develop a textile-integrated electrochemical wearable for real-time heat-strain detection at ≤1mW. It measures sweat rate, electrolytes (Na/Cl or conductivity), sweat lactate, and skin temperature, using on-garment edge AI. H₂O₂ serves as an oxidative-stress co-signal and enzyme-assay reporter, not a primary marker. The sensing stack uses printable carbon electrodes with solid-contact ion-selective and enzymatic sensors in breathable laminates; electronics are snap-in and reusable, with peel-and-stick microfluidics as the consumable. An oxidant/irritant co-monitor adds event qualification (duration–intensity product, recovery slope) to distinguish brief surges from prolonged low-level exposure. We will quantify inter-subject variability and conduct a per-user calibration; performance will be reported for within- and cross-subject evaluations. The project aligns with SPADS themes—Sensor Signal Processing and Autonomous Sensing Platforms— and draws on supervisor expertise: Dr E (electrochemical sensing; wearable integration) and Dr Escudero Rodríguez (edge artificial intelligence; signal processing). Output: a prototype targeting ≥90% F1-score in defence-relevant conditions.

Applications

First-round applications have closed and the applications for SPADS are now being considered on a gathered field basis, where applications will be considered at the end of every month until all places are filled.

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.

Full funding is available for this position.