Summary
Piers Turner is a Senior Data Analyst with a strong research background in physics, nanomaterials, computer vision and machine learning, currently developing deep learning pipelines to accelerate antimicrobial resistance diagnostics. He transitioned from applied acoustics and materials science at the National Physical Laboratory and an EngD on acoustic cavitation to postdoctoral ML-driven microscopy work at the University of Oxford, giving him a rare blend of experimental optics and algorithmic expertise. Piers builds practical tools—such as napari-bacseg, a GUI for batch segmentation and curation of bacterial microscopy—that bridge lab workflows and production models. Based in the UK with four years of focused industry and research experience, he excels at turning complex physical measurements into robust data pipelines and interpretable models. An under-the-radar strength is his hands-on knowledge of advanced acoustic measurement techniques, which informs rigorous experimental design for ML-enabled diagnostics.
4 years of coding experience
3 years of employment as a software developer
Bachelor of Science (BSc), Physics, 2:2, Bachelor of Science (BSc), Physics, 2:2 at Royal Holloway, University of London
EngD, Optimised Acoustic Cavitation for the Efficient Liquid Phase Exfoliation of 2D Nanomaterials, Passed, EngD, Optimised Acoustic Cavitation for the Efficient Liquid Phase Exfoliation of 2D Nanomaterials, Passed at University of Surrey