Research Associate in statistical signal processing for multivariate
time series - Ref:1458214
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Salary: £33,353 - £40,313 per annum
Duration of post: 24 months in the first instance
Closing date: 3rd May 2015
Project start date: 1st Jun 2015 or soon thereafter.
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Applications are invited for a 2-year post-doctoral research associate
position in the Department of Statistical Science at University College
London, UK.
This EPSRC and Innovate UK funded project will exploit exciting recent
developments in applied and computational statistics and beyond to
support regression, classification, and prediction for real-world
applications in the energy industry.
The post is available from 1st June (or as soon as possible thereafter)
and is funded up to 24 months in the first instance. It offers the
opportunity for an ambitious RA to straddle both academia and industry,
develop and publish new methodology, as well as produce algorithms which
will run in real-world products.
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* Description
The growing number and variety of low-carbon green technologies poses
new and interesting challenges for the modern, smart power grid. This
project, funded jointly by the EPSRC and Innovate UK, will draw upon
advanced time series or statistical signal processing ideas to develop
key underlying methodology for a smart sensor, event monitoring, system.
In collaboration with market-leading commercial partners including Intel
and the University of Bath, this work will contribute directly towards a
novel, marketable, product.
The work will involve several real-world problems involving multivariate
data, including regression, detection, ranking, and network/covariance
analysis.
It is likely that the techniques of interest will cross several allied
research areas. The successful candidate will have a PhD (or equivalent
qualification) and, ideally, a strong research background and
publication record in either statistical signal processing, multivariate
time series analysis, or machine learning for longitudinal data.
Candidates with an interest in one or more of the following are
particularly encouraged to apply: computational statistics or machine
learning: regression, classification, and extensions of the Lasso;
temporal/longitudinal data techniques: time series or signal processing,
etc.
Statistical techniques such as these continue to enjoy increasing
attention in many modern, so-termed, data science problems. A key driver
for this interest is the advent of recent innovations in smart
technology domains such as sensors, mobile computing, and robotics
where, for example, 'smart objects', unmanned vehicles, and sensor
networks are set to effect significant and long-lasting impact on a
multitude of sectors. Owing to the abundance of data captured from
these persistent, always-on, next-generation systems there is an urgent
and growing demand for statistically well-principled data analysis and
signal processing.
In addition to collaboration with researchers in Bath and scientists and
engineers in the partnering commercial teams there will be ample
opportunities for interaction with the immediate research group which
currently comprises two other research associates (one shared with
Cambridge University) and five research students.
The post comes with a generous travel and research expenses budget and
is funded for 24 months in the first instance.
The Department of Statistical Science at UCL offers a vibrant and
intellectually stimulating environment for individuals who wish to
develop their careers in a world-class research environment. UCL is
ranked among the top ten research institutions worldwide and has unique
strengths in Data Science, Computational Statistics, and Machine
Learning. UCL is one of five founding member of the £67M Alan Turing
Institute for Data Science. Together with the Gatsby Institute for
Computational Neuroscience at UCL, the departments of Statistical
Science and Computer Science form the Centre for Computational
Statistics and Machine Learning, (http://www.csml.ucl.ac.uk/) which is
part of the European network PASCAL (http://www.pascal-network.org/).
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* How to Apply
To apply for the vacancy please click on the "Apply Now" button at:
http://tinyurl.com/pcogjom
Informal enquiries regarding the vacancy are welcomed and may be
addressed to Dr James Nelson. See below links for contact details.
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Dr. James Nelson
Senior Lecturer
Department of Statistical Science
University College London
www.ucl.ac.uk/statistics/people/jamesnelson
www.ucl.ac.uk/~ucakjdb/
www.csml.ucl.ac.uk/people
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