[robotics-worldwide] [Jobs] Open PhD Positions at CSIRO and QUT, Australia Deadline Sep 25 2016

peym.mo peym.mo at gmail.com
Tue Sep 13 16:38:20 PDT 2016


[Jobs] Open PhD Positions at CSIRO and QUT, Brisbane, Australia


*Application deadline: Sep 25, 2016, Australian time*


Multiple PhD positions are available as a part of a research collaboration
between the Autonomous Systems Lab at the Commonwealth Scientific and
Industrial Organization (CSIRO) and two research groups at the Queensland
University of Technology (QUT), namely the Speech, Audio, Image and Video
Technologies (SAIVT) research group and the Robotics and Autonomous Systems
Research Program. All three research programs are located in Brisbane,
Australia.


Positions:


1. Dense 3D Modelling of Deformable Human Body Parts


The research in this PhD programme will focus on developing algorithms for
estimating non-rigid surface deformations of partially observable surfaces
on the moving human body.  The PhD research will include estimation of
partially observable surfaces, deformable object modeling, and tracking and
dense reconstruction of deformable objects in real-time.



2. Active 3D multi-modal situation awareness system for assistive robotics
systems


The research in this PhD topic will focus on developing enhanced
situational awareness technologies that enable assistive robotics systems
to share workspaces and collaborate with their human coworkers safely and
securely. The PhD programme will involve the development of active 3D
multi-modal (e.g., visible, thermal) systems suitable for situation
awareness and motion planning for navigation of assistive robots in a
dynamic and unstructured environment. Techniques will also be developed to
estimate and track the movements and behaviour of human workers in the
co-located environment, enabling the assistive robot to navigate safely
around human workers.


3. Agriculture Robotics (Automatic crop stress estimation)

The research in this PhD programme will focus on developing automatic crop
stress estimation in real-time using in-situ multi and hyperspectral
imaging, 3D sensing and combination of ground and ariel robots.


Position Requirements:



- MUST: a Bachelor’s degree with the *first Class Honours* or a Master’s
degree with Research in a relevant area (e.g., Computer Science, Electrical
Engineering, Mechatronics, Physics or other related fields)

- Strong competencies in one or more of the followings areas: Robotics,
Computer Vision, Machine learning, Signal Processing.

- Demonstrated strong programming skills in C++ or Python.

- Demonstrated Research Experience (for example, a good publication record)

- Experience in Robot Operating System, OpenCV and/or PCL


How to apply:

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]*

- one page cover letter explaining your research background and interests,

- CV or Resume,

- Latest Transcript


About The Autonomous Systems Program and CSIRO



The Autonomous Systems Program at CSIRO has over 100 scientists and
researchers, and is a world leader in its field. It develops foundational
and applied research in robotics, computer vision, distributed sensing and
sensor networks, and autonomous systems for a broad range of domains. It
has very well–equipped laboratories with strong engineering support, and a
variety of aerial, aquatic, wheeled and legged robotic research platforms.
The PhD projects will be conducted with joint supervision of CSIRO and QUT
researchers.



The Commonwealth Scientific and Industrial Research Organisation (CSIRO) is
Australia’s national science agency and one of the largest and most diverse
research organisations in the world. Research spans five broad areas:
information and communications; manufacturing, materials and minerals;
environment; energy; and food, health and life sciences. CSIRO provides a
highly innovative and dynamic research environment, and is positioned in
the top 1% of global research institutions in 14 of 22 research fields and
in the top 0.1% in four research fields.



For more information about CSIRO’s Autonomous Systems Program visit:

https://urldefense.proofpoint.com/v2/url?u=https-3A__research.csiro.au_robotics_&d=DQIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=Y90VcJzrn6UHdkLdotrmgekLjVLevIi9kwiGDkUslgA&s=un5iE2iQLw-xcS0NUK03Xew_eOZmDQRZ3RxpW2wBTyk&e= 


and for more information about CSIRO visit:

https://urldefense.proofpoint.com/v2/url?u=http-3A__www.csiro.au&d=DQIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=Y90VcJzrn6UHdkLdotrmgekLjVLevIi9kwiGDkUslgA&s=EQL2kkUnBgOGK0dsufaQw4RXL4TNJNQV9yY638-dMV8&e= 





About Queensland University of Technology (QUT)



Queensland University of Technology (QUT) is a leading Australian
university with “real world” focus in teaching and research and an annual
research income of more than $80M. The two PhD projects will be hosted in
the SAIVT and RAS research programs within the Science and Engineering
Faculty (SEF) of QUT.  The Faculty has around 1000 higher degree students
and provides excellent research facilities and exciting research space in
the new $230M Science and Engineering Centre.  The SAIVT and RAS research
programs sit within the School of Electrical Engineering and Computer
Science and work together in delivering world leading research in the areas
of computer vision, machine learning, image processing and robotics.



For more details about the SAIVT research program visit:

https://urldefense.proofpoint.com/v2/url?u=https-3A__wiki.qut.edu.au_display_saivt_SAIVT-2B-2BSpeech-2C-2BAudio-2C-2BImage-2Band-2BVideo-2BTechnologies-2BResearch-2Bat-2BQUT&d=DQIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=Y90VcJzrn6UHdkLdotrmgekLjVLevIi9kwiGDkUslgA&s=LTrHJH3fQo4URz2-jG3stbLYGN3v7hinPrgtAYBGdlI&e= 



and



https://urldefense.proofpoint.com/v2/url?u=https-3A__www.qut.edu.au_research_research-2Dprojects_speech-2Daudio-2Dimage-2Dand-2Dvideo-2Dtechnology-2Dsaivt&d=DQIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=Y90VcJzrn6UHdkLdotrmgekLjVLevIi9kwiGDkUslgA&s=wN7mLfytBN_bwKOUJUxfCbqEAbrfwHveqMNxuDPboSk&e= 





For more details about the QUT Robotics and Autonomous Systems (RAS) Group
please see:



https://urldefense.proofpoint.com/v2/url?u=https-3A__www.qut.edu.au_science-2Dengineering_our-2Dschools_school-2Dof-2Delectrical-2Dengineering-2Dand-2Dcomputer-2Dscience_robotics-2Dand-2Dautonomous-2Dsystems&d=DQIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=Y90VcJzrn6UHdkLdotrmgekLjVLevIi9kwiGDkUslgA&s=HFJG_mUhDx9RtKxuna_xJKadtnmc1dJ1pL_b-OGhzOo&e= 



Bests,

Dr Peyman Moghadam

Senior Research Scientist, CSIRO


Adjunct Associate Professor

School of EECS, Queensland University of Technology


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