Machine learning for design and optimization of biomolecular systems

We are looking for a doctoral student to join us on a project at the interface of machine learning and biological systems. Successful candidates will join the Biomolecular Control Group (homepages.inf.ed.ac.uk/doyarzun/) led by Diego Oyarzún.

 The project will focus on machine learning approaches to predict biological function from high-throughput data, with applications in biomedicine and biotechnology. This is a drylab project focused on the development of machine learning algorithms and data processing protocols that can deal effectively with the inherent challenges of biological data such as high signal-to-noise ratio, sparse sampling, and high-dimensionality.

 Ideal candidates should have excellent academic record and passion for quantitative methods in the life sciences. We seek open-minded and creative students keen to join a multidisciplinary team. You should have excellent mathematical and computational skills, as well as outstanding presentation skills for various audiences. Applicants must hold a First Class or an Upper Second Class degree (or equivalent overseas qualification) in a discipline relevant to the project such as machine learning, applied mathematics and quantitative biology

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