Dr Andy Downes

Senior Lecturer

Email: 

Telephone: 

+44(0)131 6505660

Location: 

2.065 Faraday Building

Engineering Discipline: 

  • Mechanical Engineering

Research Institute: 

  • Bioengineering
[photo of Andy Downes]

Biography: 

Academic Qualifications: 

PhD (Department of Engineering, University of Cambridge, 1996).

Teaching: 

Senior Fellow of the Higher Education Academy (SFHEA) since 2017.

Research Interests: 

Optical microscopy / spectroscopy

Raman spectroscopy for chemical analysis in biomedical samples (cells and tissue). Label-free microscopy (CARS, stimulated Raman, 2-photon autofluorescence, second harmonic generation), for optical imaging with chemical contrast of tissue and living cells.

Nanoscale microscopy

Atomic Force Microscopy (AFM) for imaging of biomolecules, cells and tissue. Measurement and imaging of mechanical properties on the nanoscale. Tip-enhanced optical spectroscopy and microscopy (Raman and fluorescence) at a resolution of ~10nm.

 

PhD project to start in October 2024:

Development of an accurate blood screening test for multiple cancer types using Raman spectroscopy and machine learning.

Most cancer deaths result from symptoms appearing when the tumour is at a late stage. An affordable, accurate mass screening test would find these ‘hidden’ cancers at an early stage. Some mass screening tests exist for specific cancers (e.g. bowel, ovarian) but these are not particularly accurate, and there is currently no cancer-wide test for multiple cancer types.

Raman spectroscopy uses lasers to excite vibrations at characteristic frequencies, and is a way of measuring the chemical composition without requiring expensive consumables or reagents. Our recent Raman spectroscopy data shows that we can detect stage I cancer with high accuracy, and this project would extend the work into other cancer types to pave the way for a cancer-wide screening test. The student will be trained on the spectrometer, optimise conditions, and collect spectra for blood samples of various cancer types. The data is then processed by machine learning techniques, which the student will need to enhance to separate the cancers into different types.

UK students can apply for fully-funded studentships provided by the School of Engineering (minimum 2:1 required, 4 years, deadline in late February 2024). International students should seek their own funding or scholarship.

Please contact andy.downes@ed.ac.uk for more details.