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* 3-year PhD studentship in Machine Learning
* Location: School of Computing, Newcastle University, UK
* Deadline for application: 17th of December, 2017.
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* Description
The focus of this studentship is machine learning, and specifically in
developing innovative strategies for extracting human-understandable and
valuable explanations from machine learning models.
In recent years we have seen an explosion in popularity of machine
learning (ML), both in developing new methods as well as their
successful application to a very broad range of domains covering
essentially all aspects of science, industry and society. The majority
of efforts in the ML research community focus on improving the
predictive capacity of these methods, and an often-overlooked aspect of
research is how to extract human-understandable explanations for such
predictions, as highlighted by the recent report on ML by the Royal
Society. This is especially true for arguably the fastest growing
paradigm within ML, deep learning.
In this project you will focus on designing innovative and
general-purpose strategies for extracting human-understandable knowledge
from machine learning models, particularly focusing on deep learning.
You will have access to a broad range of our own real-world datasets
from a variety of fields (biomedicine, computer security, synthetic
biology) to evaluate your methods in direct contact with the data
generators, as well as ample computational resources (High-Performance
Computing clusters, high-end GPUs) available at Newcastle University.
If you have your own idea for a PhD project within the general areas of
machine learning or big data we will be happy to consider it too. A list
of the publications of our lab, to get an idea of our lines of research,
is available at
http://homepages.cs.ncl.ac.uk/jaume.bacardit/publications.html
* Eligibility Criteria:
Applicants should have at least an upper second-class honours degree
(ideally a first class degree), or a combination of qualifications
and/or experience equivalent to that level. Ideally, students should
have a BSc or MSc degree in computer science. Applicants should be
strong programmers, and experience in machine learning/data mining/big
data/information visualisation will be greatly valued.
This award is available to UK/EU and international candidates (but
international candidates will be required to make up the difference
between the UK/EU fees and international fees). If English is not your
first language, you must have IELTS 6.5 overall (with a minimum of 5.5
in all sub-skills).
* How to apply:
You must apply through the University’s application portal
(http://www.ncl.ac.uk/postgraduate/apply/). Only mandatory fields need
to be completed. You will need to include the following information:
select 8050F as programme code
select 2017/2018 as Academic Year
select ‘PhD in Computer Science (FT) - Computer Science’ as the
programme of study
insert the studentship code COMP002 in the studentship/partnership
reference field
attach a covering letter and CV. The covering letter must state the
title of the studentship, quote reference code COMP002 and state how
your interests and experience relate to the project. Please also send
the covering letter and CV to [log in to unmask]
attach degree transcripts and certificates and, if English is not your
first language, a copy of your English language qualifications.
Funding Notes
100% of UK/EU tuition fees paid and annual living expenses of £14,553
(full award).
* Contact
For informal enquiries, please send an email to
[log in to unmask]
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Jaume Bacardit, PhD
Reader in Machine Learning
Newcastle University
The Interdisciplinary Computing and Complex BioSystems research group.
Web: http://www.ico2s.org/
Twitter: @ico2s
School of Computing, Newcastle University.
1 Science Square, Science Central, Newcastle upon Tyne, NE4 5TG, UK
Email: jaume _dot_ bacardit _at_ newcastle.ac.uk _dot_ ac _dot_ uk
Web: http://homepages.cs.ncl.ac.uk/jaume.bacardit
Twitter: @jaumebp
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