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-------- Original Message --------
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<th align="RIGHT" nowrap="nowrap" valign="BASELINE">Subject:
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<td>JOB: 3D medical imaging postdoc at Khalifa
Univ/Sharjah/UAE</td>
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<th align="RIGHT" nowrap="nowrap" valign="BASELINE">Date: </th>
<td>Sun, 10 Aug 2014 12:40:21 +0100</td>
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<th align="RIGHT" nowrap="nowrap" valign="BASELINE">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 align="RIGHT" nowrap="nowrap" valign="BASELINE">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:wp@cg.tuwien.ac.at">wp@cg.tuwien.ac.at</a></td>
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<pre>Postdoctoral position in 3D medical imaging
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Department of Electrical and Computer Engineering , Khalifa University, UAE
Net Salary $6540 per month + medical insurance + flight tickets
We are seeking a full time post doctoral research fellow to work on a KUIRF
funded project dealing with 3D medical imaging. The position is available
immediately and extends to December 2016.
The project deals with the early detection of infantile dysmorphic
syndromes (e.g. Downs syndromes) and other facial/body abnormalities.
The candidate will be working on the following tasks
1. Automatic detection of infant and body landmarks
2. Extraction of appropriate shape descriptors that can be used
for an effective identification of dysmorphic syndromes and
other potential anomalies
3. Developing and implementing appropriate and robust classification
methods that would effectively discriminate dysmorphic and normal cases.
Two different imaging modalities will be used in the above tasks, namely,
a 3D facial images and pre-natal 3D ultrasound images, in addition to
genomic and phenotype data. A Fusing approach is therefore envisaged
to integrate the outcomes of each modality as well as the genomic and
phenotype data in the decision system.
The candidate is expected to present and publish in international
peer-reviewed conference and journals, preparing research reports,
documenting software and contribute in the general welfare of the
research group.
The project will be conducted in close collaboration with the
Sheikh Zayed Institute and Children's National Medical Center
in Washington DC: (<a class="moz-txt-link-freetext" href="http://innovationinstitute.childrensnational.org/">http://innovationinstitute.childrensnational.org/</a>)
The candidate is expected to spend research stays there. He or she
will be also part of the Visual Signal Processing Research Group.
The candidate should possess a Doctorate in Computer Vision,
Machine Learning, or Applied Mathematics and a respectable
publication record (e.g. MICCAI, ICCV, ECCV, CVPR).
He or she is required to have in-depth experience with 3D medical
imaging (3D ultrasound images, mesh and depth models in particular),
robust classification, machine learning, excellent Matlab/C++
programming skills. Experience with feature extraction from 3D modalities,
Active Shape Models, and 3D shape descriptors, is great plus.
Please send :
1) A cover letter including/supporting research statement including
brief research interests, motivations and how you think your
profile best fits the position.
2) CV including two referees
to :
Dr. Naoufel Werghi
Department of Electrical and Computer Engineering, Khalifa University
<a class="moz-txt-link-abbreviated" href="mailto:Naoufel.Werghi@kustar.ac.ae">Naoufel.Werghi@kustar.ac.ae</a>
Information about Dr Naoufel Werghi can be found at
<a class="moz-txt-link-freetext" href="https://sites.google.com/site/drnaoufelwerghi/">https://sites.google.com/site/drnaoufelwerghi/</a>
Information about Khalifa University can be found at <a class="moz-txt-link-abbreviated" href="http://www.kustar.ac.ae">www.kustar.ac.ae</a>
Dr. Naoufel Werghi
Associate Professor, Electrical and Computer Engineering Department
(Sharjah Campus)
[<a class="moz-txt-link-freetext" href="cid:logo1148f347">cid:logo1148f347</a>]
Khalifa University of Science, Technology & Research (KUSTAR)
P.O. Box: 573, Sharjah, UAE
T : +971-(0)6-5978829
F : +971-(0)6-5611789
E : <a class="moz-txt-link-abbreviated" href="mailto:Naoufel.Werghi@kustar.ac.ae">Naoufel.Werghi@kustar.ac.ae</a>
--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
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