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PhD Studentship (Fixed Term)


PhD studentship in Deep Learning of disease-vector biology: hacking the mechanism of mosquito adaptation and pathogenic immune evasion.

Thanks to a grant from the National Productivity and Investment Fund and the BBSRC the University of Cambridge is able to offer four fully funded PhD's in the area of artificial intelligence and Data-Driving Economy. All projects have been created jointly by a University of Cambridge Department or Partner Institute and an Industrial Partner Company.

Successful candidates must be able to start their PhD before the end of December 2018.

Students will become part of the BBSRC DTP Cohort offering an extra level of support and training opportunities. Candidates are asked to select a project from the list below and apply to the corresponding department by the 30th June, 12 noon to be considered for one of the 4 studentships.

Short Description This project will apply deep learning and Bayesian approaches to characterizing functional elements in the mosquito genome. The predictions will be used to gain an understanding of how the malaria parasite evades the host immune system, and will be validated experimentally using structural, molecular and cell biological techniques.

Academic Supervisors - Dr Monique Gangloff and Professor Nick Gay (University of Cambridge) Industry Supervisors - Dr Jonathan Ward and Professor Thomas Hain (Fetch.ai)

Entry requirements Applicants for this research project must be UK citizens to obtain full funding. They must have obtained a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. Experience in computer coding, algorithms, data analysis is desirable.

Fixed-term: The funds for this post are available for 4 years in the first instance.

Please apply by 30th June, 12 noon to be considered for one of the 4 studentships.

Please send your application and for all enquiries to mg308@cam.ac.uk

Please quote reference PH15820 on your application and in any correspondence about this vacancy.

The University values diversity and is committed to equality of opportunity.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Further information