[Apologies if you receive multiple times this announcement]
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* Title: Mining the gene networks involved in water-stress response in
bambara groundnut: a machine learning approach to translating traits in
model species to minor crops
* Location: UK and Malaysia campuses of the University of Nottingham
* Open to: any applicant with suitable qualifications. No nationality
restrictions
* Deadline for application: As soon as a suitable candidate is identified.
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Project description:
Underutilised species have the potential to help diversify agriculture
and to make food production more robust in the face of future
challenges. The ability to use information obtained in one species to
guide evaluation of another species is the underlying principle behind
the use of model systems.
The translation of data from models and major crop species to
underutilised species is essential if underutilised species are to make
a major contribution to Global Food Security or other end-uses. The
ability to identify key components of trait networks relies on
developing methods to search very large datasets, guided by knowledge
from other systems. Machine learning techniques have been shown to be
very competent at this task, as they are able to explore vast datasets
to identify key genes and their interactions. Moreover, they can easily
integrate multiple sources of knowledge and automatically identify the
relevant parts of the system being analysed.
This project will focus on the use of machine learning and
bioinformatics techniques to study the process of water-related stress
in bambara groundnut (an African legume) by contrasting datasets from
this species with the known networks of model organisms. This legume
grows successfully with varying access to water, cropping from the Namib
desert in Africa to the humid tropics in Indonesia.
Applicants should have a 2.1 or 1 class honours degree, or a combination
of qualifications and/or experience equivalent to that level and have
training in data mining techniques or bioinformatics. Previous biology
experience will be an advantage for Computer Science applicants. The
successful candidate should be confident working within and across a
range of activities, have excellent organisational abilities, be
enthusiastic and have good interpersonal skills.
The student will spend time at the UK and Malaysia campuses of the
University of Nottingham. At UK the student will be based at the
Interdisciplinary Computing and Complex Systems (ICOS) research group
(http://icos.cs.nott.ac.uk) at the School of Computer Science. In
Malaysia, the student will be co-hosted by Biosciences at UNMC
(www.nottingham.edu.my/biosciences/index.aspx) and the new Crops for the
Future Research Centre currently under construction.
The student will be registered formally at The University of Nottingham
Malaysia Campus. The studentship provides full tuition fees and a
monthly stipend of 4400MYR (Malaysian Rynggit), for a duration of 3 years.
This studentship will remain open until a suitable candidate is found,
thus we recommend applying early.
Supervisor names and contact details :
Festo Massawe, School of Biosciences, UNMC ([email protected])
Jaume Bacardit, School of Computer Science, UoN
([email protected])
Sean Mayes, Plant and Crop Sciences, UoN ([email protected]))
Michael Holdsworth, Plant and Crop Sciences, UoN
([email protected]) )
For informal enquiries about this studentship please contact
[email protected] - Web: http://www.cs.nott.ac.uk/~jqb/
Please quote I.D. code Bam1-004 on all correspondence.
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Jaume Bacardit, PhD
Lecturer in Bioinformatics
University of Nottingham
Interdisciplinary Computing and Complex Systems Research Group,
School of Computer Science, Jubilee Campus, Nottingham, NG8 1BB, UK
URL: http://icos.cs.nott.ac.uk
Twitter: @ICO2S
Tel: +441158467044
Fax: +441159516292
Email: jaume _dot_ bacardit _at_ nottingham _dot_ ac _dot_ uk
Web: http://www.cs.nott.ac.uk/~jqb
Twitter: @jaumebp
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