Connectionists: Fwd: PhD position in machine learning

[Richard Turner]

Dear Connectionists,

Please see below for details about an open PhD position at the University
of Cambridge Machine Learning Group supervised by Dr. Richard E. Turner
<http://cbl.eng.cam.ac.uk/Public/Turner/WebHome>, Dr. Aditya Nori
<https://www.microsoft.com/en-us/research/people/adityan/> (Microsoft
Research) and Prof. Andrew Blake <https://www.turing.ac.uk/ablake/>.

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
<http://mlg.eng.cam.ac.uk/>, supervised by Dr. Richard E. Turner
<http://cbl.eng.cam.ac.uk/Public/Turner/WebHome>. Dr. Aditya Nori
<https://www.microsoft.com/en-us/research/people/adityan/> (Microsoft
Research) and Prof. Andrew Blake <https://www.turing.ac.uk/ablake/> will
co-supervise. The funding for this position comes from the Microsoft
Research PhD Scholarship Programme
<https://www.microsoft.com/en-us/research/academic-program/phd-scholarship-europe-middle-east-africa/>
.

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
<http://www.graduate.study.cam.ac.uk/how-do-i-apply> 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.
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