<div dir="ltr"><div dir="ltr"><div dir="ltr">
<p class="MsoNormal" style="text-align:justify"><font face="arial, sans-serif"><span lang="EN-GB" style="color:black">[Jobs]
Multiple </span><span lang="EN-GB" style="color:black">PhD </span><span lang="EN-GB" style="color:black">positions
in the Deep Learning for Robotics at CSIRO and ANU, Australia <span></span></span></font></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif"> <span></span></font></span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">Application
deadline: <b>Aug 20, 2019</b>, Australian
time<span></span></font></span></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif"> <span></span></font></span></p><p class="MsoNormal" style="text-align:justify"><font face="arial, sans-serif"><span lang="EN-GB" style="color:black">Multiple
</span><span lang="EN-GB" style="color:black">PhD </span><span lang="EN-GB" style="color:black">positions
are available as a part of a research collaboration between the Robotics and
Autonomous Systems group at the Commonwealth Scientific and Industrial
Organization (CSIRO) (in the top 1% of global research institutions) and the Australian
National University (ANU) (Ranked #1 in Australian University) Australia. You
will receive a scholarship of $28,000 per year (+$10,000 top-up per year,
+$5000 conference fund per year) for 3.5 years all Tax Free! These are ongoing
positions to be filled at any time before the deadline. Students are
expected to spend time at both institutes and publish at the top tier journals
and conferences during their PhD. <span></span></span></font></p><p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif"> <span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><b><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">1. Self-Supervised Learning for 3D
Multimodal Perception <span></span></font></span></b></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">Potential
impact of deep learning is limited due to the lack of large, annotated, and
high-quality datasets in domains of interest. Annotating such datasets is
laborious, costly and time-consuming. This project proposes to develop
self-supervised learning systems to extract and use the relevant context given
by strong prior spatio-temporal models (e.g. dense 3D reconstructions) as
supervisory signals in training. This new concept will investigate model
structures that encodes spatio-temporal data, and show rapid adaptation of
models to new domains (few-shot learning) using trained embeddings layers
(self-supervised, or prior data).<span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif"> <span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><b><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">2. Deep SLAM <span></span></font></span></b></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">Simultaneous
Localization and Mapping (SLAM) is a key enabling component of driverless
vehicles, robotics and augmented reality. The SLAM goal is to estimate pose of
the vehicle and simultaneously generate dense 3D scene reconstruction. At CSIRO
we have developed and deployed state-of-the-art 3D LiDAR-based SLAM systems for
the past decade. There is a new direction of research at the intersection of
deep learning and geometry-based 3D SLAM. The research in this PhD programme
will develop algorithms for geometry-based Deep Learning SLAM in a dynamic and
unstructured environment. The PhD programme will involve the development of
self or semi-supervised learning methods to address the significant weakness of
most current deep networks. <span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><span><font face="arial, sans-serif"> </font></span></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><b><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">3. Hyperspectral Deep Learning<span></span></font></span></b></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">Hyperspectral
cameras are currently undergoing a change from bulky and expensive equipment
towards mobile and portable devices. A hyperspectral camera comprises of
hundreds of bands with shortwave dependencies. Compared to conventional colour
cameras (RGB bands), one could use these shortwave dependencies to design and
develop a deep network for object classification, semantic segmentation and
scene understanding. Both spectral and spatial relationship needs to be
modelled by the deep networks simultaneously. The research in this PhD
programme will develop algorithms for hyperspectral deep learning. The PhD
programme will involve the development of learning with self-supervision
algorithms to address the significant weakness of most current deep networks. <span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><span><font face="arial, sans-serif"> </font></span></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><b><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">Position Requirements:<span></span></font></span></b></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><span><font face="arial, sans-serif"> </font></span></span></p><p class="gmail-MsoListParagraphCxSpFirst" style="text-align:justify;line-height:12.75pt"><font face="arial, sans-serif"><span lang="EN-GB" style="color:black"><span>·<span style="font-style:normal;font-variant-caps:normal;font-weight:normal;font-stretch:normal;line-height:normal">
</span></span></span><span lang="EN-GB" style="color:black">Must have a Bachelor’s degree with
the first Class Honours or a Master’s degree with Research in a relevant area
in the past 5 years (e.g., Computer Science, Electrical Engineering,
Mechatronics, Physics or other related fields)<span></span></span></font></p><p class="gmail-MsoListParagraphCxSpMiddle" style="text-align:justify;line-height:12.75pt"><font face="arial, sans-serif"><span lang="EN-GB" style="color:black"><span>·<span style="font-style:normal;font-variant-caps:normal;font-weight:normal;font-stretch:normal;line-height:normal">
</span></span></span><span lang="EN-GB" style="color:black">Strong competencies in one or more of
the followings areas: Robotics, Computer Vision, Machine learning, Deep
Learning.<span></span></span></font></p><p class="gmail-MsoListParagraphCxSpMiddle" style="text-align:justify;line-height:12.75pt"><font face="arial, sans-serif"><span lang="EN-GB" style="color:black"><span>·<span style="font-style:normal;font-variant-caps:normal;font-weight:normal;font-stretch:normal;line-height:normal">
</span></span></span><span lang="EN-GB" style="color:black">Demonstrated strong programming
skills in C++ or Python in Linux.<span></span></span></font></p><p class="gmail-MsoListParagraphCxSpMiddle" style="text-align:justify;line-height:12.75pt"><font face="arial, sans-serif"><span lang="EN-GB" style="color:black"><span>·<span style="font-style:normal;font-variant-caps:normal;font-weight:normal;font-stretch:normal;line-height:normal">
</span></span></span><span lang="EN-GB" style="color:black">Demonstrated Research Experience e.g.
a good publication record.<span></span></span></font></p><p class="gmail-MsoListParagraphCxSpLast" style="text-align:justify;line-height:12.75pt"><font face="arial, sans-serif"><span lang="EN-GB" style="color:black"><span>·<span style="font-style:normal;font-variant-caps:normal;font-weight:normal;font-stretch:normal;line-height:normal">
</span></span></span><span lang="EN-GB" style="color:black">Demonstrated Experience in Robot
Operating System, Tensorflow and/or Pytorch.<span></span></span></font></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif"><span> </span><span></span></font></span></p><p class="MsoNormal" style="text-align:justify;vertical-align:baseline"><b><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">How to apply<span></span></font></span></b></p><p class="MsoNormal"><span lang="EN-GB"><font face="arial, sans-serif">Prospective students should send the
following documents in a SINGLE PDF file to Dr. Peyman Moghadam
(peyman.moghadam AT csiro.au) with the subject [PhD ANU], including:<span></span></font></span></p><p class="gmail-MsoListParagraphCxSpFirst" style=""><font face="arial, sans-serif"><span lang="EN-GB"><span>·<span style="font-style:normal;font-variant-caps:normal;font-weight:normal;font-stretch:normal;line-height:normal">
</span></span></span><span lang="EN-GB">a current c.v.<span></span></span></font></p><p class="gmail-MsoListParagraphCxSpMiddle" style=""><font face="arial, sans-serif"><span lang="EN-GB"><span>·<span style="font-style:normal;font-variant-caps:normal;font-weight:normal;font-stretch:normal;line-height:normal">
</span></span></span><span lang="EN-GB">details of grades or an
academic transcript<span></span></span></font></p><p class="gmail-MsoListParagraphCxSpLast" style=""><font face="arial, sans-serif"><span lang="EN-GB"><span>·<span style="font-style:normal;font-variant-caps:normal;font-weight:normal;font-stretch:normal;line-height:normal">
</span></span></span><span lang="EN-GB">one page cover letter
explaining your research background and interests,<span></span></span></font></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><span><font face="arial, sans-serif"> </font></span></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><span><font face="arial, sans-serif"> </font></span></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">Bests,<span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">Adjunct
Prof. Peyman Moghadam<span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif">CSIRO<span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif"><span> </span><span></span></font></span></p><p class="MsoNormal" style="text-align:justify;line-height:12.75pt"><span lang="EN-GB" style="color:black"><span><font face="arial, sans-serif"> </font></span></span></p><p class="MsoNormal">
</p><p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="color:black"><font face="arial, sans-serif"> </font></span></p>
</div></div></div>