We are seeking a highly creative and motivated PhD student to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK.
This project aims at creating new Bayesian optimization (BO) algorithms that use semi-supervised learning for making better predictions in high-dimensional structured spaces, enabling the solution of complex optimization problems in engineering design. Our contributions will be in the areas of generative modelling of data, Bayesian neural networks, approximate inference and Bayesian optimization.
The Machine Learning Group is internationally renowned, comprising about 30 researchers, including Dr. José Miguel Hernandez Lobato, Prof. Zoubin Ghahramani, Prof. Carl Rasmussen, Dr. Turner and Dr. Adrian Weller.
Applicants should hold (or be expected to hold) a degree in Information Engineering, Electrical Engineering, Statistics, Physics, or Computer Science preferably with 1st class honours (or equivalent). Some practical experience of machine learning or statistics would be strongly preferred (e.g. course work assignments or research).
This studentship will cover all Univeristy fees and a maitenance allowance of at least £14,582 per year for UK students, EU citizen are eligible for a fees only award.
Overseas students are not eliggible for this studentship and should not apply. .
Applications should be submitted via the University of Cambridge Graduate Admissions web pages http://www.admin.cam.ac.uk/students/gradadmissions/prospec/apply/, with Dr. José Miguel Hernández Lobato) identified as the potential supervisor
The University values diversity and is committed to equality of opportunity.