PhD position in machine learning

[Richard Turner]

Dear ML news,

Please see below for details about an open PhD position at the University of Cambridge Machine Learning Group supervised by Dr. Richard E. Turner, Dr. Aditya Nori (Microsoft Research) and Prof. Andrew Blake. 

Best wishes,

Rich

PhD Fellowship in Computer Vision and Machine Learning

Deep learning has revolutionised the field of computer vision, but requires access to large homogeneous datasets. Humans in contrast can learn new concepts from remarkably few labeled examples by leveraging information from a diverse set of sources (unlabelled examples, related tasks, etc.). This ability has been termed visual fast mapping in the psychology literature. The goal of this PhD project is to develop new machine learning techniques that support visual fast mapping being data-efficient and having the ability to leverage information from many different data sources. The new techniques will be tested on data sets of medical images and scenes for autonomous systems. The research is expected to impact both medical imaging and the way people interact with and train AI systems.
 

The PhD position will be based in the Cambridge Machine Learning Group, supervised by Dr. Richard E. Turner. Dr. Aditya Nori (Microsoft Research) and Prof. Andrew Blake will co-supervise. The funding for this position comes from the Microsoft Research PhD Scholarship Programme.

We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in computer vision and machine learning. 

A typical duration of a PhD in the machine learning group is four years.

Applicants must formally apply through the GRADSAF system at the University of Cambridge by the deadline, indicating “PhD in Engineering” as the course and denoting 'Turner' as the supervisor. This position is fully funded for UK and EU students. 

Deadline: May 21st 2018

Applications from outstanding individuals may be considered after this time, but this may adversely impact your chances for admission. Moreover, applications will be considered on a rolling basis and 

Further information about completing the admissions forms:

The Machine Learning Group is based in the Department of Engineering, not Computer Science.

We will assess your application on three criteria:

academic performance (make sure to ensure evidence for strong academic achievement e.g. position in year, awards etc.)
references (clearly your references will need to be strong, they should also mention evidence of excellence as quotes will be drawn from them)
research (detail your research experience, especially that which relates to machine learning and computer vision)

The form asks for a research proposal. Here we would like you to read around the research area and develop some initial ideas in this direction. We do not offer individual advice or feedback on the proposal as it is part of the assessment and want to be fair to all candidates.  The research proposal should be about 2 pages long and can be attached to your application (you can indicate that you proposal is attached in the 1500 character count Research Summary box). This aspect of the application does not carry a huge amount of weight so do not spend a large amount of time on it. Please also attach a recent CV to your application too.