Physics-informed and physics-constrained machine learning for next generation imaging

Physics-informed and physics-constrained machine learning for next generation imaging.
A team of researchers from the University of Glasgow and the "big image data" company, Dotphoton. The student will be part of a multidisciplinary team of physicists and working on novel imaging techniques, of computer scientists working on novel machine learning approaches that encode the physics of the imaging problem and bio-engineers working with cutting edge microscopy techniques. The ambition is to develop new-generation, physics-constrained AI that can image better, faster and more intelligently that current systems. By embedding physical constraints in to the design of the AI, you will develop better microscopes and biological imaging techniques that will be tested on new-generation fluorescence microscopes and healthcare monitoring devices. The research will be carried out at the Advanced Research Centre (ARC) in Glasgow, where you will work with a team of physicists, computing scientists, engineers and biologists. The project will be in close collaboration with Dotphoton (Switzerland) and will ideally involve also in-person visits to the company premises to work with their team of data scientists.