Advanced Spectroscopy and Machine Learning for Classifying Complex Phenotypes
Supervisors:
Prof Alberto Sanz Montero, School of Molecular Biosciences
Dr Neal Dawson, School of Biodiversity, One Health & Veterinary Medicine
Dr Mario Gonzalez Jimenez, School of Chemistry
Summary:
Are you interested in combining fundamental biology, state-of-the-art spectroscopy, and machine learning to uncover complex biological phenotypes across diverse populations? If so, this could be the ideal PhD project for you.
You will work on a set of complementary projects where you will:
• Develop new machine learning algorithms to identify individuals carrying different types of mitochondrial defects.
• Estimate the age of wild vertebrate species using just tiny amounts of blood and advanced spectroscopic techniques.
• Apply your trained algorithms to drug discovery, identifying compounds that restore mitochondrial function and slow ageing across species.
You will be supervised by a multidisciplinary team of three supervisors, each bringing expertise in molecular biology, physiology, and chemistry. This unique training environment will equip you with cutting-edge skills in experimental biology, spectroscopy, and computational analysis. Alongside technical expertise, you will gain fundamental skills in data handling, critical thinking, and scientific communication, with tailored mentoring to help you realise your full potential and career ambitions.