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PHD STUDENTSHIP: COMPUTER VISION AND MACHINE LEARNING IN THE UNIVERSITY OF EDINBURGH

Country/Region : UK - United Kingdom

Website : http://homepages.inf.ed.ac.uk/hbilen

Description

We are seeking an exceptional UK/EU PhD candidate to study in the prestigious in the Institute of Perception, Action and Behaviour (IPAB) at the University of Edinburgh. The successful candidate will have an opportunity to work on cutting-edge computer vision and machine learning research projects using Deep Learning. The goal of this project is to develop the next generation of deep learning systems for computer vision with a focus on multiple-task learning from videos. The successful candidate will have the opportunity to collaborate with leading computer vision and machine learning groups in the UK and Europe.
PhD candidate requirements: We are looking for creative and motivated applicants with, or expected to obtain soon, a 1st Class Honours degree in a relevant discipline, including Informatics, Computer Science, Electrical Engineering but not limited to. Basic programming skills (python, c++, MATLAB) are required. Previous experience on machine learning and computer vision, for example object and action classification, is appreciated but not a requirement.
Funding: This is a University of Edinburgh funded award and will provide an annual stipend for three years of £14,553 per year (subject to confirmation), plus University fees for UK/EU students. Any eligible non-EU candidates must fund the remainder of the overseas tuition fee.
Application: If you are interested in the position, please provide a CV, a personal statement detailing your research interests and reasons for applying (max 1 page), marks for your degree(s) and an email address for one academic reference. The application deadline is November 17, 2017 and the expected start date for the position is February 2018. All documents should be in electronic format and sent via e-mail to hbilen-AT-ed.ac.uk.
Dr Hakan Bilen
http://homepages.inf.ed.ac.uk/hbilen

Last modified: 2017-10-08 13:24:21