[Dear colleagues, i would be grateful if you can disseminate this advert
through your channels]
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* Two 3-year PhD studentship in Machine Learning for Synthetic Biology
* Location: School of Computing, Newcastle University, UK
* Start date: By September 2018
* Deadline for application: 13th of March, 2018.
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* Value of award
100% of UK/EU tuition fees paid and annual living expenses of
£14,553(full award). Successful international candidates will be
required to make up the difference between the UK/EU fees and
international fees.
* Description
These PhD studentships are part of the Portabolomics project. The vision
of Portabolomics (https://portabolomics.ico2s.org/) is to bring forth a
breakthrough in Synthetic Biology that will enable the development of
portable biocircuits across chassis (i.e. from one bacteria species to
another). This vision is akin to the Java virtual machine having enabled
the reuse and portability of software across different operating systems
and hardware platforms.
In this doctoral project you will focus on the challenge of devising
innovative strategies to transform the vast volumes of data generated in
the wet lab experiments of Portabolomics into actionable knowledge that
can feed into the computational work on network analysis and
verification in the project. The data generated by the project is vast
and diverse: imaging data, omics data, complex and heterogeneous
annotation from public and private sources. Using a combination of
biological data integration, state-of-the-art machine learning,
knowledge extraction and information visualisation techniques we seek to
build methods to identify biomarkers and infer biological networks.
The specific topic of each studentship will be decided based on the
skill set of the successful applicants, although we envision that they
will require a combination of the following:
- Strong machine learning background and proficiency in the state of the
art data science languages (e.g. R, python)
- Deep Learning
- Knowledge discovery
- Biological data integration
- Information visualisation
- High Performance Computing (e.g. classic HPC clusters, GPUs, Intel
PHI, Big Data frameworks, Cloud resources).
* Eligibility Criteria:
Applicants should have 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/biological data will be
greatly valued.
* How to apply
You must apply through the University's Application Portal. Only
mandatory fields need to be completed. You will need to include the
following information:
select 8050F as programme code
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.
* Contact
For informal enquiries, please email [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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