Research position (PhD or postdoc) on scalable mining Oxford University
Research position (PhD or postdoc) on scalable mining of uncertain data streams
Title: HiPerDNO Data Mining Research Associate
Grade: 7 (Salary in range £ 28,983 - 35,646pa)
This position is based at the Oxford e-Research Centre
(OeRC, http://www.oerc.ox.ac.uk)
and within the EC FP7 'High Performance Distributed Network Operation'
(HiPerDNO) project, which brings together researchers in electricity
distribution networks, electrical engineering, and computing science
from Brunel, IBM Haifa, and Oxford, as well as European energy
companies (EDF, Electricite de France, Union Fenosa, Indra, Gtd,
Korona, Elektro Gorenjska, and Iset).
Future electricity distribution networks with mass deployment of
network equipment sensors and instrumentation, millions of smart
meters, small-scale embedded generation, and responsive load will
generate vast amounts of data requiring near to real-time analysis. It
is the aim of this project to develop a new generation of distribution
network management systems that exploit novel near to real-time high
performance computing (HPC) solution. The approach of this project is
to employ cloud computing that will enable scalable data mining,
feature extraction, and near to real-time state estimation.
Duties and Responsibilities:
The position will be concerned with research and implementation of
cutting edge data processing techniques within an HPC environment.
The successful candidate will primarily collaborate with
Dr. Dan Olteanu of the Oxford University Computing Laboratory,
(http://www.comlab.ox.ac.uk/people/Dan.Olteanu)
who will lead the project research on uncertain data mining. It is also
expected that the post-holder will closely work with the Parallel
Systems position within the OeRC on this project to ensure that the
implementation of their algorithms and software is optimised for
performance and use of resources on the HPC systems made available.
HiPerDNO is an international collaboration; hence it is required to
travel to meetings at the various partner sites for both shorter and
longer durations. That includes the HiPerDNO final year
demonstrations and on-site tests.
The post-holders main duties will include:
* Undertake research and development in the area of mining uncertain
data streams with the techniques to be implemented on HPC
architectures;
* Collaborate closely with Dr Dan Olteanu on data management
research and with the parallel systems team to optimise the efficiency
of the developed algorithms and software;
* Take responsibility for dissemination of project deliverables
through the project website, events, and publications;
* Publish in appropriate journals and conferences the results of
developed systems and software.
Selection Criteria
Candidates will be judged on the basis of the following criteria and
their applications should address each point to show how their
experience and skills meet the criteria. We encourage applications at
both PhD and postdoc level.
Essential Criteria:
* A higher degree, preferably a doctorate, in a relevant
subject such as Computing Science, Engineering Science, Physics,
Mathematics or equivalent industrial experience;
* Knowledge/experience of the following:
- Detailed knowledge of data management theory and/or systems.
- Good knowledge of machine learning and/or data mining techniques.
- Good programming skills using modern languages and technologies;
* Track record of published work appropriate to your age and work experience;
* Experience of carrying out independent research/development.
* Willingness to work effectively as a team member and to supervise
less experienced team members, should the occasion arise.
* Good communication skills, both oral and written.
Desirable Criteria:
* Knowledge of uncertain/probabilistic data management;
* Parallel systems (including hardware), environments and computing;
* Knowledge/experience in power system engineering.
Further details:
Requirements under UK Border Agency's points-based migration system:
1. Points requirement
Applicants who would need a work visa if appointed to the post are
asked to note that they will need to demonstrate that they have
sufficient points, and in particular that:
* they have sufficient English language skills (evidenced by
having passed a test in basic English, or coming from a majority
English-speaking country, or having taken a degree taught in English)
* that they have sufficient funds to maintain hemselves and any
dependants until they receive their first salary payment.
Further information is available at:
http://www.ukba.homeoffice.gov.uk/workingintheuk/tier2/generalarrangements/eligibility/
2. Data protection
All data supplied by applicants will be used only for the purposes of
determining their suitability for the post and will be held in
accordance with the principles of the Data Protection Act 1998 and the
University.s Data Protection Policy.
Please send completed application form, CV and with covering letter
to: the Personnel Manager, OeRC, 7 Keble Road, Oxford OX1 3QG
(tel: 01865 610621 fax: 01865 610624)
email: recruitment@oerc.ox.ac.uk
Complete applications must be received by 12 noon on March 24th, 2010.
Applicants should note the OeRC will only reimburse full travelling
expenses within the British Isles for those candidates selected for
interview. Any offer of employment will be subject to the
satisfactory completion of a medical questionnaire.
Oxford University is an Equal Opportunities Employer.
Title: HiPerDNO Data Mining Research Associate
Grade: 7 (Salary in range £ 28,983 - 35,646pa)
This position is based at the Oxford e-Research Centre
(OeRC, http://www.oerc.ox.ac.uk)
and within the EC FP7 'High Performance Distributed Network Operation'
(HiPerDNO) project, which brings together researchers in electricity
distribution networks, electrical engineering, and computing science
from Brunel, IBM Haifa, and Oxford, as well as European energy
companies (EDF, Electricite de France, Union Fenosa, Indra, Gtd,
Korona, Elektro Gorenjska, and Iset).
Future electricity distribution networks with mass deployment of
network equipment sensors and instrumentation, millions of smart
meters, small-scale embedded generation, and responsive load will
generate vast amounts of data requiring near to real-time analysis. It
is the aim of this project to develop a new generation of distribution
network management systems that exploit novel near to real-time high
performance computing (HPC) solution. The approach of this project is
to employ cloud computing that will enable scalable data mining,
feature extraction, and near to real-time state estimation.
Duties and Responsibilities:
The position will be concerned with research and implementation of
cutting edge data processing techniques within an HPC environment.
The successful candidate will primarily collaborate with
Dr. Dan Olteanu of the Oxford University Computing Laboratory,
(http://www.comlab.ox.ac.uk/people/Dan.Olteanu)
who will lead the project research on uncertain data mining. It is also
expected that the post-holder will closely work with the Parallel
Systems position within the OeRC on this project to ensure that the
implementation of their algorithms and software is optimised for
performance and use of resources on the HPC systems made available.
HiPerDNO is an international collaboration; hence it is required to
travel to meetings at the various partner sites for both shorter and
longer durations. That includes the HiPerDNO final year
demonstrations and on-site tests.
The post-holders main duties will include:
* Undertake research and development in the area of mining uncertain
data streams with the techniques to be implemented on HPC
architectures;
* Collaborate closely with Dr Dan Olteanu on data management
research and with the parallel systems team to optimise the efficiency
of the developed algorithms and software;
* Take responsibility for dissemination of project deliverables
through the project website, events, and publications;
* Publish in appropriate journals and conferences the results of
developed systems and software.
Selection Criteria
Candidates will be judged on the basis of the following criteria and
their applications should address each point to show how their
experience and skills meet the criteria. We encourage applications at
both PhD and postdoc level.
Essential Criteria:
* A higher degree, preferably a doctorate, in a relevant
subject such as Computing Science, Engineering Science, Physics,
Mathematics or equivalent industrial experience;
* Knowledge/experience of the following:
- Detailed knowledge of data management theory and/or systems.
- Good knowledge of machine learning and/or data mining techniques.
- Good programming skills using modern languages and technologies;
* Track record of published work appropriate to your age and work experience;
* Experience of carrying out independent research/development.
* Willingness to work effectively as a team member and to supervise
less experienced team members, should the occasion arise.
* Good communication skills, both oral and written.
Desirable Criteria:
* Knowledge of uncertain/probabilistic data management;
* Parallel systems (including hardware), environments and computing;
* Knowledge/experience in power system engineering.
Further details:
Requirements under UK Border Agency's points-based migration system:
1. Points requirement
Applicants who would need a work visa if appointed to the post are
asked to note that they will need to demonstrate that they have
sufficient points, and in particular that:
* they have sufficient English language skills (evidenced by
having passed a test in basic English, or coming from a majority
English-speaking country, or having taken a degree taught in English)
* that they have sufficient funds to maintain hemselves and any
dependants until they receive their first salary payment.
Further information is available at:
http://www.ukba.homeoffice.gov.uk/workingintheuk/tier2/generalarrangements/eligibility/
2. Data protection
All data supplied by applicants will be used only for the purposes of
determining their suitability for the post and will be held in
accordance with the principles of the Data Protection Act 1998 and the
University.s Data Protection Policy.
Please send completed application form, CV and with covering letter
to: the Personnel Manager, OeRC, 7 Keble Road, Oxford OX1 3QG
(tel: 01865 610621 fax: 01865 610624)
email: recruitment@oerc.ox.ac.uk
Complete applications must be received by 12 noon on March 24th, 2010.
Applicants should note the OeRC will only reimburse full travelling
expenses within the British Isles for those candidates selected for
interview. Any offer of employment will be subject to the
satisfactory completion of a medical questionnaire.
Oxford University is an Equal Opportunities Employer.
