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<td>[Edinburghvisionec] JOB: Edinburgh postdoc in visual
behaviour understanding</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Date: </th>
<td>Tue, 15 Sep 2020 14:51:29 +0100</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">From: </th>
<td>Bob Fisher <a class="moz-txt-link-rfc2396E" href="mailto:rbf@inf.ed.ac.uk"><rbf@inf.ed.ac.uk></a></td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:EdinburghVisionEC@inf.ed.ac.uk">EdinburghVisionEC@inf.ed.ac.uk</a></td>
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<br>
<br>
JOB: Edinburgh postdoc in visual behaviour understanding <br>
Applications are invited for a Research Associate in Visual
Behaviour Understanding<br>
in the School of Informatics, University of Edinburgh.<br>
The School of Informatics, located in the heart of Edinburgh, is
the largest<br>
institution of this kind in the UK and one of the largest in
Europe.<br>
See: <a class="moz-txt-link-freetext" href="https://www.ed.ac.uk/informatics/">https://www.ed.ac.uk/informatics/</a><br>
<br>
The application area of the computer vision research to be
undertaken by<br>
this researcher is non-intrusive monitoring of ageing people in
their own<br>
home or in a care home situation.<br>
<br>
The research will be undertaken in the recently formed Advanced
Care Research<br>
Centre (ACRC) at the University of Edinburgh, a cross-university
centre focussing<br>
on the technological, medical, and sociological issues needed to
support the<br>
day-to-day living of ageing people. This project will part of the
ACRC's New<br>
Technologies of Care research programme and the post-holder will
be primarily<br>
based at the Edinburgh BioQuarter.<br>
<br>
This full-time position is fixed term for 30 months.<br>
<br>
Informal enquiries to be directed to Professor Bob Fisher:
<a class="moz-txt-link-abbreviated" href="mailto:R.B.Fisher@ed.ac.uk">R.B.Fisher@ed.ac.uk</a><br>
or Professor Ram Ramamoorthy: <a class="moz-txt-link-abbreviated" href="mailto:s.ramamoorthy@ed.ac.uk">s.ramamoorthy@ed.ac.uk</a><br>
<br>
Salary grade scale: UE07 : 33,797 - 40,322 GBP / year<br>
<br>
Feedback is only provided to interviewed candidates.<br>
<br>
Closing date is 5pm (GMT) on 14th October 2020.<br>
Vacancy Reference: 053187<br>
See:
<a class="moz-txt-link-freetext" href="https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.display_form">https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.display_form</a><br>
<br>
Further Information<br>
<br>
The data will come from RGBD cameras and other sensors (some
wearable,<br>
some embedded). One responsibility of the researcher will be to
develop<br>
several reliable video analysis components oriented around colour
and possibly<br>
depth imagery taken from fixed cameras in an indoor environment.
The lighting<br>
would not be controllable, so the analysis would have to cope with
a variety<br>
of lighting conditions, including direct sunlight from outside, as
well as changing<br>
locations and source types of indoor lighting. The purpose of the
analysis is to<br>
detect events such as falls, lack of activity such as arising from
a medical<br>
situation, and quantifying the level of activity at different time
scales.<br>
Frame rates will be low, e.g. 5 frames per second; however all
processing will<br>
need to be done at video rates on low power GPUs and CPUs, such as
on an NVidia<br>
Jetson Nano. The components would need to be integrated into a
larger<br>
hardware/software system, and evaluated as part of that larger
system.<br>
<br>
The second responsibility is in the area of activity modelling
methods and<br>
sequential decision making. The activity modelling task is
targeted at understanding<br>
what an elderly person is doing, quantifying the amount of
activity at different<br>
time scales and using these models for advice giving and coaching.
While similar<br>
to the analysis described above, in this case the analysis will
also take into<br>
account additional signals, such as from accelerometers and
gyroscopes embedded<br>
in wearables. The sequential decision making research will
investigate advanced<br>
methods for determining when a notifiable event has occurred, how
to build causal<br>
models of such events and how this can be turned into actionable
advice to the<br>
various involved stakeholders.<br>
<br>
_______________________________________________<br>
Edinburghvisionec mailing list<br>
<a class="moz-txt-link-abbreviated" href="mailto:Edinburghvisionec@inf.ed.ac.uk">Edinburghvisionec@inf.ed.ac.uk</a><br>
<a class="moz-txt-link-freetext" href="http://lists.inf.ed.ac.uk/mailman/listinfo/edinburghvisionec">http://lists.inf.ed.ac.uk/mailman/listinfo/edinburghvisionec</a><br>
<br>
<pre class="moz-signature">--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
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